This PDF file contains the front matter associated with SPIE Proceedings Volume 12249, including the Title Page, Copyright information, and Table of Contents.

Recently, the security and scalability challenges of traditional internet of things systems are emerging as the wide application of IoT in logistics, warehousing, smart home, etc. The traditional IoT systems are built on centralized architecture which is highly vulnerable to the single point of failure and network attacks. Fortunately, the blockchain offers a reliable security solution for IoT systems due to its decentralized architecture, cryptographic schemes, and consensus algorithms. However, there are two main challenges when integrating blockchain technologies into the IoT system: First, IoT devices have limited resource capabilities. Second, an IoT system generally contains massive devices. In this paper, to address the challenges mentioned above, we proposed a lightweight blockchain for resource-constrained IoT devices. Proof of authentication (PoAh) consensus algorithm and DAG-based blockchain architecture were adopted in our proposed system. The performance, power consumption, and resource usage of the proposed blockchain system are verified by numerous experiments. The experimental results show that the proposed system was lightweight and suitable for resource-constrained IoT devices.

In recent years, with the popularization of 5G communication technology and the rapid growth of data traffic and network bandwidth, aiming at the problem of large CPU (Central Processing Unit) processing burden and low occupancy in communication protocol processing, this paper uses TOE (TCP Offload Engine) technology to implement the protocol on ZYNQ hardware. TOE technology is to unload TCP/IP protocol processing and execute it on hardware, and convert C/RTL (Register Transfer Level) code through high-level integrated HLS (High Level Synthesis). The results show that the accelerated processing method based on TOE protocol can greatly reduce the CPU occupation rate. Compared with the traditional CPU processing method, the performance is improved by 8.9%. Compared with the traditional RTL level design and implementation method, the development difficulty is reduced and the resource occupation rate is reduced by 9.7%.

This paper proposes a simulation model of lane-changing that considered indirect reciprocity at intersection in Internet of Vehicles environment. The model attempts to address the problem of drivers' reluctance to cooperate in lane changes at intersections by introducing an image scoring system. The core of the system is that lagging vehicles can improve their image score by yielding to lane changing vehicles, thus gaining a greater chance of being yielded to in the future. This paper proposes a Q-learning based reinforcement learning algorithm that extends the model to a repeated evolutionary game, which means that drivers are able to continually evaluate gains and adjust their strategies. The conclusions are summarised below. Such a lane change mechanism, which considers indirect reciprocity, does improve the cooperation of non-fully rational drivers and saves lane change time. driver cooperation improves the operational efficiency of intersections, especially at high penetration of connected vehicles and medium to high traffic densities.

In this paper, we study a load balancing optimization method for joint user association and UAV location in UAV-aided wireless communication networks. First, we propose a utility function that takes the users’ SINR, UAV loads, and the spatial dispersion of the users served by the identical UAV into account. Second, this paper achieves load balancing by solving the utility maximization problem. Due to the coupled user association and the location of the UAV in the utility function, the utility maximization problem is a non-convex mixed integer nonlinear problem (MINLP), which is inconveniently solved. Therefore, we decouple the original problem into two sub-problems. In the first step, given the UAVs’ location, we can obtain the users’ association scheme based on the utility-maximizing association strategy (UMS). In the second step, based on the current users’ association scheme, we update the UAVs’ location through an improved distributed in-order location optimization method (DOLO). Finally, by solving the user association and UAV location optimization sub-problems iteratively, we can obtain the optimal user association scheme and UAV location. The simulation results show that, compared with the traditional user association method, the proposed method can achieve load balancing efficiently. Meanwhile, it can guarantee better dense effect between users and the UAVs that serve them.

Safety is one of the most important requirements of home for people. Burglary or outbreak of fire may cause serious consequences in terms of finance and life safety. The paper designs and implements an IOT enabled wireless home security system using Raspberry Pi (RPI) to make residences more secure. The home security system is full-featured including real-time video surveillance, email notification when visitors detected, opening the door through face recognition, monitoring smoke in rooms and alerting. A Raspberry Pi with two cameras, a passive infrared (PIR) sensor and an ultrasonic sensor is placed in front of the door. A NodeMcu with a smoke detection sensor is placed in rooms. The two microcontrollers can send data through Internet to a server and then data can show on the APP. Users can monitor their home and respond according to situations through the APP from anywhere in the world.

Fire seriously threatens people's property and life safety and hinders the development of society. Therefore, it is necessary for fire prevention institutions to strengthen the monitoring of fire hazards. Internet of Things technology has three major features: comprehensive perception, reliable transmission and intelligent processing. Combined with the fire-fighting robot, they can solve the problems of personal safety, insufficient data collection and real-time feedback that firefighters often face when implementing fire hazard and rescue. This project studies a fire-fighting robot detection system based on Internet of things technology, which can replace fire-fighting and rescue personnel to enter the scene of dangerous disasters for detection and reconnaissance, and provide reliable basis for rescue work. At the same time, it also provides some technical schemes for promoting the design and implementation of intelligent fire hydrant monitoring system.

Valve, as an important part of pipeline control system, is gradually developing towards the goal of electric and intelligent with the development of technology and the trend of the Internet of Things. In this case, the traditional way of manually supervising the valves and pipes appears to be costly and inefficient and thus is no longer applicable. Therefore, this paper proposes a new way to monitor the status of the valves by developing a remote monitoring and control system for electric valves based on Internet of Things. The system is powered by the wind and solar hybrid electricity generation module and managed by STM32F429. The status data of the valve and related environmental parameters detected by field sensors can be collected by MCU through RS485 and UART and are then encrypted and sent to the remote server through a 4G module. To ensure the security of data transmission, a hybrid encryption algorithm based on ECC and AES is implemented and verified in the embedded system, which uses AES to shorten the encryption time of large amount of plaintext and uses ECC to encrypt the AES key to solve the security shortcomings of AES, thus increasing the security of data transmission.

The creation of a complete Internet of Things system involves knowledge of multiple discipline systems, which is relatively complex. In response to this situation, this article introduces a safe and efficient IoT system construction process. First, it uses Wi-Fi technology for data transmission, and sends data collected by sensors to EMQX running on a cloud server through a wireless network. In order to have a flexible processing of the data, we use the Spring Boot framework to develop a Java backend, run the RabbitMq message queue to receive and process the EMQX data, and save it to the Mysql database. In addition, use the Vue front-end framework to develop web applications to realize remote real-time monitoring of data.

China's economy is in an important transition period of rapid development and high-quality development. The contradiction between water resources allocation and regional economic development needs has become a major strategic problem faced by the national economy and the people's livelihood. In this paper, the industrial structure effect that affects the change of regional water use intensity is decomposed into industrialization effect, industrial structure upgrading effect, tertiary industry water-saving technology effect, and domestic water extraction effect from the spatial dimension. The LMDI decomposition expansion model of regional water use intensity is constructed. Taking the Yangtze River Economic Belt as an example, the influence mechanism of industrial structure upgrading on the spatial dimension difference of water use intensity is deeply explored. The study shows that since 2016, the improvement of the level of industrial structure upgrading in each province and city can inhibit its increase in water consumption intensity compared with that in Shanghai. Jiangxi, Hunan, Yunnan, and Sichuan need to optimize the allocation of water resources among industries, especially between the primary and secondary industries. Anhui, Jiangxi, Chongqing, Yunnan, and Sichuan need to improve the service level of the tertiary industry.

Aiming at solving the security problems of data confidentiality and integrity in the traditional centralized Internet of things communication, data leakage and tampering caused by malicious users abusing communication functions in the Internet of things system, a data communication mechanism of Internet of things based on blockchain is proposed. Combined with the characteristics of blockchain, such as decentralization, immutability and auditability, the data exchange mechanism of Internet of things communication tunnel is proposed. Preventing malicious communication through communication tunnel management and control of data exchange between devices, and ensures data integrity in combination with digital signature technology. The security analysis shows that the mechanism has good security characteristics and meets the security requirements of Internet of things communication. Experiments on Ethereum show that compared with existing studies, this mechanism has less time overhead, indicating the feasibility and availability of this mechanism.

Home care is the most effective and widely used traditional care model, but it also has great limitations. Through the study of "embedded" smart care service, it is found that it can effectively make up for the shortcomings of traditional home care. Finally, through analytic hierarchy process, the problems existing in the combination of embedded smart care and traditional home care are found, and countermeasures and suggestions are put forward.

While industrial wireless technology optimizes the communication performance of the industrial network, security has also become a key problem restricting the popularization of an industrial wireless network communication application. As an industrial wireless network protocol independently developed in China, the WIA-PA standard urgently needs to establish a set of independent and controllable security mechanisms. Aiming at the security problems faced by industrial wireless WIA-PA networks, this paper proposes a secure communication scheme based on National secret algorithm, designs node identity authentication, key agreement, and end-to-end secure transmission suitable for WIA-PA networks, and develops a secure communication system based on National secret algorithm based on self-developed chip TF2400 and WIA-PA protocol stacks, the feasibility of the proposed communication scheme and the test results of the confidentiality of the network show the effectiveness of the proposed secure communication scheme.

IoT devices collect large amounts of industrial and personal data, which can raise serious privacy and security concerns. Due to storage constraints, IoT devices need to upload the collected data to a third party's cloud server for storage. This situation would severely limit the data owner's ability to manage the data. If the data is uploaded directly, the data owner cannot guarantee that the service provider will not disclose and sell this data, which could lead to a data breach. In this paper, we formalize an encrypted access control framework for large-scale time-series data access control in IoT scenarios based on puncturable attribute-based encryption. The scheme allows data owners to share time-series data collected by IoT devices at a fine-grained level, while ensuring the confidentiality of the data during transmission and storage. The decryption keys can repeatedly be updated to revoke the recipients' ability to decrypt a selected message, or a message created during a specific time period. Through careful protocol design and implementation, the computational efficiency of the proposed scheme is comparable to the state-of-the-art method with the same functionalities. Encryption can be done in about several hundred milli-second, decryption takes only about tens of millisecond and the time required for decryption is constant.

With the construction of smart cities, schools around the country have started a large-scale informatization reform. The redundancy of paper data and the complexity of management make the "student information management system" become one of the key concerns of school information reform, and it has important practical significance to conduct indepth research on it. This paper studies a kind of student information management system which realizes back-end operation based on database and adopts the technology of front and back end separation. The characteristics of the system are simple page, cheap operation and practical function. This paper also analyzes the necessity and feasibility of the system design in detail, describes the database design of the system and the realization of the specific functions of the information management system.

Today, some areas of China still maintain traditional farming patterns. Although some modern materials have entered this field, many activities still occur in the process of farming and management. This article aims to explore the design of digital agriculture and the cultivation of materials based on the Internet. The research and implementation of this plan has promoted the integration of Internet of Things technology, computer technology and agriculture, and further promoted the application process of advanced technologies such as the Internet of Things. Complying with the culture of rapid development of the Internet of Things technology, combining sensor technology and embedded communication technology to develop smart products will not only benefit farmers, but also promote the implementation and promotion of Internet of Things technology. Through the collection, analysis and link control function of sensor data, the accurate and timely intervention of nuclear elements such as electricity, humidity, carbon dioxide and so on in the process of plant development can be controlled in time to meet the requirements of plant growth. There are 6 sets of total samples, one set of samples and actual results There are differences, and the results are within the allowable range.

The protection of historical buildings is becoming more and more complicated, and the traditional methods of historical building protection cannot keep pace with the development of the times. At the technical level, it encounters layers of obstacles and lacks digital technical means and information management methods. Architects only rely on subjective experience to repair and design, and cannot accurately judge the pros and cons of historical building protection schemes. Faced with these problems, this paper analyzes the virtual reality technology, and describes the technology and its development and application in the field of architectural heritage protection. The 3D construction method of cultural relic buildings based on virtual interaction is studied, and the development and optimization of the 3D virtual interactive system for architectural heritage is proposed. With the continuous application of virtual reality technology in the field of architectural heritage protection, it will play a huge role in improving the research level of the entire field and developing the application of virtual reality technology.

Monitoring systems have been extensively applied in many industrial domains. With fast development of IoT technology, there are many practical demands to establish monitoring systems based on IoT platform. This paper presents a general architecture of traditional monitoring system that includes Device Level, Server Level and Client Level, and discusses its primary functions to provide a general understanding of monitoring system. And then components and functions of IoT platform are introduced and explained. A new general architecture of monitoring system based on IoT platform is proposed. The new architecture has Device Level, IoT platform Level and Client Level, and inherits traditional hierarchy structure that is easy to understand and apply in practice. A practical case of the new architecture is given to prove that the new architecture is correct and practical.

With the rapid development of Internet of Things communication technology, the application of big data technology can improve the application level of Internet of Things communication technology to a certain extent. In the operation process of the Internet of Things communication big database, its operation speed and processing efficiency are the important foundation to improve the Internet of Things communication big data and application benefits. In order to improve its running speed and processing efficiency, the semi-structured data identification method can be analyzed based on the Internet of Things communication database. In the specific research process, it is necessary to study the specific situation of semi-structured data and explore the main characteristics of semi-structured data. By analyzing the sparsity coefficient and sparsity subspace of data in large database, we can master the correlation characteristics of different data. According to the semi-structured data structure, we can use the combination of principal component analysis and Delphi algorithm to form a comprehensive weighting method to scientifically determine the index weight in the process of semi-structured data identification. This recognition method can reduce the data rewriting rate and ensure the reliability of recognition results, and its practical application value is also prominent.

Aiming at the problems of single lamp control mode in traditional lighting system, monotonous light color display, and difficulty in meeting people's demand for high-quality life, an intelligent lighting control system based on iOS was designed and implemented. Use low-energy Bluetooth Mesh networking technology to uniformly manage, control, and personally change the color of multiple lighting devices; use OpenCV image processing technology to take pictures of smart lighting devices and switch the lighting devices on the photos After the operation processing of color adjustment and light intensity adjustment, the real image control that the lights in the photos on the mobile phone screen and the lighting effects of the physical lamps change simultaneously are realized, creating an immersive lighting experience and increasing the playability of smart lighting.

In recent years, deep learning technology has been widely used in computer vision tasks, and has achieved great success in the fields of vision detection and tracking. On this basis, the landing of deep learning technology has become an urgent problem to be solved in the next step. Video target detection and tracking is an important direction in the field of computer vision. It combines the knowledge of image processing, mathematical analysis, probability density analysis and other fields, and is widely used in security, medical care, video surveillance, intelligent transportation and other fields. It realizes the intelligent analysis of the movement of external objects by using computers instead of human eyes, which provides great convenience for human life and work. Because of its unique charm, sports programs are widely welcomed by the public in today's society. Target detection and tracking in football game video is a very challenging task, and has good practical and commercial value. At present, the technology of target detection and target tracking has become more and more mature, but the complex environment, serious occlusion and multi-target tracking have become the main obstacles to the development of video moving target detection and tracking. These bottleneck problems make the application of computer vision in intelligent manufacturing unable to give full play to the best efficiency. Therefore, it needs to be systematically analyzed and solved.

Taking the design of residential retrofit for aging as the research object, this paper studies the design method for aging based on BIM technology. By describing the housing problems faced by the aging population in China and analyzing the difficulty of the renovation design for the aging of the existing housing, the paper proposes to solve the problems in the renovation design by using BIM technology from the aspects of modular design, roaming simulation, collision detection and intelligent housing data collection.

With the successive introduction of the country's strategic goals of carbon peaking and carbon neutrality, the development and promotion of ultra-low energy consumption buildings will undoubtedly become a new trend in the construction industry. Based on the introduction of the application to solar photovoltaic roofing in ultra-low energy consumption buildings, this paper takes "Sanya Science and Technology Park Rest station Design" as an example to introduce the main application and application forms of solar photovoltaic technology in tropical regions. The use of solar photovoltaic is simulated, and effective measures are proposed to optimize the overall use of solar photovoltaic power generation, improve the utilization efficiency of photovoltaic power generation, and provide relevant ideas and references for the application of solar photovoltaic roofing in ultra-low energy consumption buildings.

In the fiercely competitive market environment, retail enterprises are supposed to deeply optimize their supply chains and improve service quality. The Internet of Things has a good application effect in the supply chain collaboration and the realization of information and process sharing. This paper constructs a theoretical model of internal integration, external integration and firm performance. Using the operational data of 230 retail enterprises in China, the structural equation modeling is used to demonstrate the impact of supply chain integration on retail enterprise performance. The empirical results show that both internal integration and external integration are positively affecting firm performance, and internal integration has a strong positive effect on external integration. This clarifies the steps for retail companies to integrate their supply chains. On this basis, the specific application of the Internet of Things in internal and external integration is analyzed, which is of positive significance for retail enterprises to improve their operating level, reduce losses, and enhance market competitiveness.

As an important material basis, energy is related to the rapid and stable development of the economy and society. Taking the new round of energy revolution as a development opportunity, establishing an advanced energy supply system with the goal of being safe, reliable, cost-effective, clean and environmentally friendly has become a development goal pursued by all parts of the world. In order to deal with the dual problems of energy crisis and environmental pollution, the establishment of the Energy Internet is imminent, which has led to the concern of the reliability level of energy supply. Over the past 300 years, with the continuous deepening of the self-industrialization process, the energy industry has developed rapidly, providing strong support for the development and progress of the world economy and society. The energy Internet covers the interaction of various information and energy, and it is difficult to evaluate it with traditional reliability assessment methods. This paper adopts the method of data mining, which is based on many disciplines such as machine learning, pattern recognition, statistics, database and artificial intelligence. and industry attention.

With the continuous development of water information technology, the application of emerging information technology to achieve intelligent management of water resources is practical and feasible. This paper describes the application of Internet of Things technology in intelligent water resources management to achieve intelligent management and improve the efficiency of water resources system management.

With the development of society and the acceleration of urbanization, the innovative concept and practice of smart cities have been widely promoted. The construction of smart communities is an important part of smart city construction and an inheritance, development and implementation of the smart city concept. However, China's intelligent community construction has not yet formed a unified information management platform, community services can not achieve a high degree of intelligence, it is difficult to meet the growing multi-level and diversified needs of community residents living services. Therefore, based on the rapidly developing information technology of Internet of Things and computer application technology, this paper designs and develops a intelligent community management information system in order to improve the management of community services, achieve efficient management of intelligent communities, improve the quality of life of community residents, and achieve the goal of "five types" of communities that are liveable, safe, healthy, civilized and harmonious, providing a regional demonstration for the construction of smart cities with the community as the unit, and advancing the development process of China's socialist modernisation.

In terms of the current situation where individual lamp control and monitoring system is of high delay, low reliability, and inconvenient maintenance when using power line communication, an individual lamp control and monitoring system based on wireless communication is proposed in this paper. Through the research on the overall structure design, fault maintenance mechanism, antenna housing design, and deployment of the individual lamp monitoring and control system, an individual lamp control and monitoring system based on wireless communication that meets the standards with high reliability and easy maintenance is designed and applied in an airport in Guangdong. In addition, through the tests on the performance and function, the system design verification has been completed, which lays the foundation for applying the individual lamp control and monitoring system based on wireless communication to the IV-level light guidance function of the A-SMGCS system and the construction of the runway status lights system.

More and more precast utility tunnels with large cross-sections and complicated structural styles have been built with the blowout growth of utility tunnels in China and its vigorous advocacy of "green building". The precast segmental construction technology of underground utility tunnels has incomparable advantages compared with conventional utility tunnels. This paper introduces a piece of smart construction equipment for precast tunnels which mainly includes five main structures - excavation and support cabin, segment assembly cabin, backfill support cabin, roof platform, and gantry crane, seven systems - thrusting system, articulated steering system, clamping system, grouting system, articulated sealing system, tail sealing system and monitoring system and other supporting systems. The finite element models of excavation and support and segment assembly cabins are established. It is verified that no part of the equipment exceeds the yield strength of Q345 and that the stress and strain are within the allowable range. This paper provides a reference for the smart construction of urban underground utility tunnels.

Road transportation plays a leading role in the transportation system with its convenient, direct access and large coverage area, and the quality of road engineering directly affects the interaction between the economies of various regions. Among them, the quality of road base pavement engineering plays a significant and critical role in the quality of road engineering. To further ensure the high quality construction and development of road engineering, this paper designs and develops a road base pavement engineering management information system based on computer application technology. The system realizes the control of road base pavement engineering information, road construction materials, engineering quality, construction personnel management and road engineering maintenance by means of information technology, which is conducive to the construction unit's scientific decision and management of road base pavement engineering and facilitates the construction unit to improve the quality of road base pavement engineering.

Food quality and safety has now become a global problem. Products traceability system helps to find the factors affecting products quality in time and reduce losses when products quality problems are found. Warehousing is an important part of products traceability system, and its storage environment directly affects the quality of products. A warehouse monitoring system based on the internet of things is presented in this paper, which is composed of STM32 microcontroller, temperature and humidity sensor, Wi-Fi module, RFID skimmer, alarm circuit, OLED display and Aliyun platform. The temperature and humidity of the storage environment and the information that products are discharged from warehouse and warehousing are captured through the temperature and humidity sensor and RFID skimmer, and then the collected information are sent to the Aliyun platform. When the temperature or humidity exceeds the threshold, the system will automatically give an alert. This system lays the foundation for the products traceability system.

With the development and prosperity of tourism, outbound tourism is becoming more and more popular. When people are ready to travel, the formulation of tourism routes is an important and key step. Although people can check the relevant travel guides or collect relevant information online, it is not only a waste of time and inefficient, but also the information found will not be consistent with their current needs. With the progress of the times, deep learning has developed rapidly in recent years, especially in image and text processing. This brings new inspiration to the research of recommendation system. This paper studies the dynamic tourism route recommendation based on the deep learning algorithm. The dynamic tourism route recommendation can be effectively solved through the obtained data, the established model and algorithm. Further, through the experimental comparison with different variants of the depth model, the experimental results show that the combination of the model also has better recommendation performance than other variants of the depth model, The effectiveness of the model combination is verified. This has laid a good foundation for the promotion and use of tourism service recommendation system.

Long-term care insurance is a medical insurance system that provides reimbursement for the insured who need long-term care due to the loss of all or part of certain functions of the body due to old age, disease or disability. The medical insurance department allocates insurance funds monthly according to the number of patients served by medical institutions. Due to the fraudulent acts of a few medical institutions, the long-term care insurance funds have suffered losses. This paper establishes an early warning model for fraudulent insurance based on the consistency of fraudulent behaviors in medical institutions, and applies the frequent pattern mining Apriori algorithm. First, the sample data is used to generate frequent itemsets. Combining the actual service distance, service location, doctor's orders and other information to verify the association rules of frequent itemsets, the association rules and behavior models of long-term care insurance fraud are determined, and a feasible method to identify long-term care insurance fraud is given.

Aiming at solving the problems of easily stolen manhole covers or equipment in the well, delayed manual inspection, high operation and maintenance cost, and easy tilt posing a safety hazard for electricity wells, an intelligent manhole cover monitoring system based on NB-IoT technology was designed. Positioning technology is one of the important technologies in intelligent manhole cover monitoring system. In order to achieve accurate positioning of manhole cover, time difference of arrival (TDOA) positioning Algorithm is applied to intelligent manhole cover monitoring system. The TDOA positioning algorithm used in this paper is based on Taylor series, which calculates the position based on the target initial position, and has better positioning accuracy. Simulations are implemented, and the results show that positioning accuracy of the algorithm in this paper is about 5 m and this positioning algorithm can realize the positioning of intelligent manhole cover.

Urban functional zone plays an important role in understanding complex urban systems. However, discovering urban functional zones is still challenging due to the complexity of urban systems. In recent years, the emergence of high spatial resolution (HSR) remote sensing image and human sensing data has provide favorable conditions for urban functional zone study. These two types of data have their own characteristics. Remote sensing images can describe the naturalphysical characteristics of ground elements; and human sensing data can describe the characteristics of human socioeconomic activities. Many researches have used either of them for urban studies, but few studies consider combining those two characteristics. In this paper, we propose to integrate HSR remote sensing image and smart card data of public transportation to analyze urban functional zones by combining the characteristics of ground elements and residents travel. The method was used to discover the urban functional zones of the Chaoyang district, Beijing, China. The result was compared with the results of the methods using HSR remote sensing image and smart card data separately. It demonstrated that our strategy is more effective.

Aiming at the problems of signal security and network energy consumption in the data transmission process of intelligent electric manhole cover, a low-power secure transmission method of intelligent electric manhole cover based on edge computing is proposed in this paper. Firstly, the transmission mode of each node is determined according to the location of each edge node and the maximum transmission power, with the goal of maximizing the safety capacity. On this basis, the transmission path is determined according to the data size collected by the intelligent electric manhole cover and the processing capacity of each node, with the goal of minimizing network energy consumption.

The goal is to maximize customer time satisfaction andminimize the cost of site selection establish a mixed integer programming model. a hybrid immune simulated annealing algorithm is designed to improve the search efficiency of the algorithm. Taking the fresh demand point of fresh agricultural products in an area as an example, the optimal location scheme of pre warehouse is obtained. The results show that the time satisfaction of the obtained scheme is increased by 13.6% and 3.4% respectively compared with that of the immune algorithm and simulated annealing algorithm, and the total cost of location is reduced by 5729 and 8297 yuan respectively. The hybrid immune simulated annealing algorithm can accelerate the convergence speed, obtain higher time satisfaction and lower total cost of location, which provides a reference for the location of pre warehouse.

At present, ‘One-stop Service’ has been widely used in government services. Some colleges have also created a campus version of ‘One-stop Service’ for teachers and students. This paper analyzes the difficulties in realizing ‘One-stop Service’ in some colleges that adopt the internal and public network model, and proposes a comprehensive plan to build a set of cross-network data exchange platform, a global data center covering all networks, and a unified intelligent fusion portal platform covering the whole school. This solution can help such colleges achieve ‘one-stop service’.

Deterministic Networking (DetNet) is a new network architecture proposed by IETF DetNet working group for industrial Internet of Things and other application scenarios. And its high-reliability and low-latency communication services need to adopt multi-constrained multi-path non-overlapping routing algorithm. Because it is different from the existing routing algorithms on the Internet, it is an important topic to study routing algorithms that meet the requirements of DetNet. Based on the routing characteristics of DetNet, we studied a multi-routing algorithm-—RMCDP_RD algorithm. Aiming at the problem that the algorithm can't calculate non-overlapping routes in some cases, the algorithm is improved. By introducing Tarjan algorithm, the efficiency of the improved algorithm is improved. The algorithm is verified and tested in the simulation environment, and the results show the effectiveness of the improved algorithm.

With the rise of smart cities, classification and identification of fruits and vegetables in unmanned supermarkets has become a hot spot in recent years. In order to improve the efficiency of fruit and vegetable classification and recognition in practical applications, this paper proposes a lightweight ResNet-50 fruit and vegetable recognition method, which integrates a deep separable convolution module into the residual module of the ResNet-50 network, which makes the classification model more lightweight, improves the recognition efficiency, and is better applied to mobile devices or in a microcomputer. At the same time, the network model is fine-tuned and optimized to ensure that the classification model still maintains a high accuracy rate after being lightweight. In the end, under the premise of ensuring high recognition precision, the recognition speed of this method is increased from 6.4s to 5.2s. Compared with the original network, the recognition speed is increased by 19.19%, and the model weight file size is reduced by 57.8%.

In order to promote the digitalization of the power grid, many smart meters are installed on the distribution network side to monitor the operating status of the power grid and equipment information in an all-round way. Frequent data missing phenomenon will lead to misjudgment in the thematic analysis of abnormal electricity consumption in distribution network. In this paper, a missing data reconstruction method based on Improved Bayesian Ridge Regression (IBRR) is proposed. Regularization methods are added to the posterior distribution estimation of parameters to automatically filter redundant information in massive data, thereby avoiding Overfitting phenomenon of maximum likelihood estimation, and improve model training speed and generalization ability. A mutation processing mechanism is proposed for the abnormal fluctuations in the reconstruction results. The results show that, compared with the traditional method, the proposed method has better reconstruction accuracy, and the reconstruction speed is greatly improved.

Demand-side energy management relying on load monitoring technology is an important guarantee for promoting smart grid construction. Non-intrusive load decomposition (NILD) technology has received a lot of attention worldwide due to its low cost, easy maintenance and high security. In this work, we propose a neural network combining an on/off state classification subnetwork with a power regression subnetwork. We incorporate a tailored self-attention module into the power regression subtask to improve the generalization of the model. The experimental results show the proposed deep neural network outperforms other SGN models.

In order to give full play to the high parallel and high efficiency characteristics of heterogeneous signal processing platforms, relevant scholars at home and abroad have proposed many task scheduling algorithms with their own advantages to improve processing efficiency. However, for communication intensive tasks, the existing task deployment methods are no longer applicable because of their higher communication requirements and communication delay becomes the key to limit the performance of the platform. For communication-intensive signal tasks, this paper proposes a load balancing scheduling method based on edge clustering. Tasks are abstracted as directed acyclic graph, we aggregate the qualified task edges according to the rating function to reduce the computational complexity, and task duplication is used to replicate the tasks on the critical path to reduce communication overhead and dynamically balance processor load. Through the experimental verification of random task graphs and radar task, it is concluded that the algorithm has a good scheduling result for communication intensive tasks, which can achieve good processor load balancing and system scheduling length reduction.

In the process of water quality monitoring, qualitative evaluation can be carried out according to the changes in the number of underwater animals and the state of motion and other parameters, because of the underwater image resolution is low, mistracking and loss can occur when tracking underwater targets, this paper proposes a matching algorithm based on scale invariant feature transform (SIFT) and nuclear correlation filter (KCF) of underwater target tracking algorithm. SIFT algorithm was used for feature extraction to obtain the detection frame, and the improved HOG feature was used for KCF training and tracking. According to the experimental results, it can effectively detect and track underwater fish under complicated underwater conditions.

With the improvement of construction technology and the rapid development of society and economy, highway tunnels show the features, such as large dimensions and lengths in structure, rapidly increased traffic volume, large vehicles for transportation of dangerous goods, and increased moving speed, leading to the occasional serious incidents, which poses great threat to the operational safety of highway tunnels. Taking the northern extended tunnel of Yingbin Avenue in Hangzhou area as an example, this study integrates the technologies such as the Internet of Things based sensor monitoring and artificial intelligence to obtain and analyze the characteristics of tunnel traffic flow, aiming to study the characteristics of traffic environment changes when traffic accidents occur in the tunnel. The results show that: 1) the operation and maintenance management platform based on digital monitoring for the tunnel can handle the problems regarding monitoring and characterization in terms of multiple facilities, multiple sources of information, and multiple types of vehicle behaviors in the complex environment of the tunnel, to ensure the interconnection and communication among the various devices in the tunnel; 2) the system can realize one-click emergency response with respect to incident disposal, which can shorten the disposal time and can select, add, start and stop the plan, to form a log storage, therefore, it can provide the necessary technical support for the safe, efficient, and environmentally-friendly operation of traffics in the tunnel.

Data aggregation is one of the most commonly used privacy protection schemes for smart grids, and smart meters will inevitably fail. Therefore, fault tolerance helps to improve the robustness of data aggregation schemes. Existing solutions often require the trusted third parties. Therefore, a fault tolerance privacy-preserving data aggregation scheme (FPDA) based on blockchain for smart grid is proposed. An improved Practical Byzantine Fault Tolerance (PBFT) is used to select a data collection unit (DCU) from all DCUs as a mining node (MN) to construct piece. The scheme protects users' private data while achieving fault tolerance without relying on any trusted third party. Analysis of security and performance shows that our scheme can achieve security and fault tolerance while ensuring the cost of lightweight computing and communication.

With the digital transformation and development of the medical industry, how to protect data security effectively and reduce privacy data leakage is an important issue in the age of digital healthcare. The paper mainly analyzes security risks under the digital medical model. The digital medical data security protection system is proposed to ensure the security of medical data, combined with data identification, data encryption and decryption, data desensitization, data security audit and other technologies.

The anti-theft work of fishery farms has always been the focus. There are many loopholes in traditional methods and it will consume more manpower and material resources. This article try to use a target detection network based on YOLOv4 to identify people and ships above water. The precision (P), recall rate (R), a combination of points of different precision and recall rate AP, and the harmonic mean value of precision and recall rate F1 are used as index evaluations, and finally the trained weights are used to predict pictures. Last, a nice detection effect is obtained. The results show that the use of this network for fishery anti-theft has a wonderful effect.

Modern water systems are augmented by the application of advanced information and communications technology. However, this trend has brought with it the problem of coordinating the flow of data between the various subsystems. This paper argues that Building Information Modelling (BIM) software can be used to improve interoperability and form the basis of a smart water management system (SWMS). The paper begins with an introduction that outlines the problem of the “information island” in current smart water management systems and suggests BIM as a possible solution. The Literature Review describes current research on smart water management systems, the current use of BIM, and then identifies how BIM has the potential to improve the integration of the components of smart water management systems.

In view of the current construction site, the steel bar inventory work is still using manpower counting method, the process is cumbersome, time-consuming and inefficient. YOLOv5s algorithm was used to train the rebar counting lightweight model, Mosaic data was used to enhance the data set, and CSP structure was used to enhance the feature extraction ability of the model. Compared with the existing mainstream lightweight models such as YOLOV3-Tiny and Mobilenet-SSD, the mAP of YOLOv5s reached 0.994. In order to overcome the impact of complex environment and better apply to smart site, the model was deployed to Mobile devices using Pytorch Mobile framework. In the test set, the counting accuracy of the mobile application of reabar inventory is above 0.98, and the detection effect is equivalent to that of the server. Experimental results show that YOLOV5s intelligent reabr counting model deployed to mobile terminal has good detection accuracy and accuracy.

The smart city 3D visualization management platform based on big data technology realizes the scene display of various objects and data under the jurisdiction of government departments with the help of 3D geographic information fusion technology. Build a Google Earth style three-dimensional panoramic display of the earth, realize the level-by-level visualization from the earth to provinces, cities, districts and counties, parks to key buildings, realize the three-dimensional visualization of geographic information base map, roads, buildings, water system, contour terrain, key buildings, etc. Display the spatial distribution and density of each facility component in the urban three-dimensional scene, intelligently monitor, analyse and mine the status data and operation data of equipment and facilities in combination with big data technology, so as to realize intelligent perception and decision support. The smart city technology architecture is divided into four layers: perception layer, network layer, data layer and application layer. The perception layer is composed of PC, mobile terminal and various sensors to collect and monitor the information data of urban transportation, communication, energy, environment and life. It is characterized by "ubiquitous perception". The network layer is mainly composed of Internet, Internet of things, communication network, radio and television network and other basic communication facilities. It provides "efficient transmission" of urban information anytime and anywhere through wired and wireless broadband networks. The data layer is the brain of the smart city, which manages the core asset of the city - data. The data layer adopts cloud computing technology, combined with the construction of four basic databases such as economy, population, legal person, geography and professional databases such as transportation, public security, education and medical treatment, to provide "intelligent" services such as data sharing, data mining, data analysis, decision support and statistical analysis, so as to effectively support intelligent decision-making. The application layer consists of smart government, smart industry and smart people's livelihood, including e-government, digital urban management, smart transportation, smart tourism and smart community. When building smart applications, we need to be people-oriented and select the required smart applications scientifically and reasonably in combination with urban development planning.

With the rapid development of computer technology, community governance shows intelligence and modernization, and the intelligence of community governance plays an important role in the construction of an intelligent city. How to measure the degree of community intelligence has become a problem to be discussed. Based on the questionnaire data, this paper comprehensively evaluates the degree of community intelligence by using Topsis modified by entropy weight and gives suggestions from the perspectives of government, community, and residents.

The “People’s City” is proposed under the background of China’s urban development. The 54 digital information related with “People’s City” were selected by SPSS.20, and were explored through Chi-square test and Cross-tabulation analysis. It is found that the variables of the report year (P<0.001), the newspaper level (P<0.001), the information source (P<0.001) and the report city (P<0.001) showed significant differences, and “Shanghai” (N=27) will become the digital model of “People’s City”. Moreover, “governance”(word frequency weighting=0.853) and “construction” (word frequency weighting=0.825) are the core issues of the “People’s City”. Based on these data results, more diversified digital image of the “People’s City” should be more considered.

China is a large e-commerce country. The development of cross-border e-commerce requires the improvement of crossborder logistics. The overseas warehouse model promotes the development of cross-border logistics and is conducive to the localization of cross-border trade. The location of overseas warehouses should comprehensively consider various issues such as warehouse construction costs, transportation costs, delay fees, taxes and fees, and establish a multi-objective planning model based on the total operating cost and delay time cost of the overseas warehouse logistics model. Ecommerce business data analysis, using NSGA-II algorithm to solve the model. Adjust the different parameters of NSGAII to verify the stability of the algorithm solution, and call the Gurobi solver to compare the accuracy of the NSGA-II solution, and provide a reference for overseas warehouse location.

There are many researches on the relationship between transportation infrastructure construction and urban economy. Most of them believe that investment in transport infrastructure can promote urban development and economic growth. This paper studies the feedback mechanism between traditional waterway construction and economic development. However, the empirical results show that the construction of the Yangtze Waterway does increase GDP, but not by increasing shipping volume. The reasons for this phenomenon are analyzed, and it may be that the existing waterway restricts the navigation of large ships, or that the waterway transportation has been replaced by other transportation modes due to the rapid development of other transportation modes. Water transport has always been less economical than other modes of transport. A new feedback mechanism is also proposed.

Shared parking, which can make full use of the free time of private or non-private parking slots, has become an effective way to ease the pressure of urban parking. Under the condition of shared parking, the traditional parking generation rate model can no longer accurately predict the demand of urban parking slots. Therefore, this paper analyzes and studies the parking choice behavior of residents in the sharing mode, and uses machine learning algorithms such as XGBoost and decision tree to predict the demand for parking shared parking spaces.

In order to analyze the feasibility of the cutter head directly cutting reinforced concrete and the characteristics of parameter changes during the cutting process in the pipeline renewal project. This article uses mechanics and mathematics methods to study the calculation method of cutting resistance and torque starting from the mechanism of the spherical gear cutting of reinforced concrete pipes. This paper designs a cutter head test, systematically studies the changing laws and influencing factors of cutting parameters, and proposes guidance parameters for tunnelling control. The results show that: when the cutterhead cuts the reinforced concrete pipe in full section, the cutterhead thrust, torque and time have an exponential function relationship. By increasing the rotation speed of the cutter head, the thrust of the cutter head gradually decreases, and the torque decreases first and then increases. Combining the cutting parameters of the cutter head and the cutting specific energy, it is determined that the rotation speed of the cutter head is 2.5~3.5r/min and the cutting speed of the cutter head is 18~24mm/min as reasonable cutting parameters.

With the "one belt, one road" initiative and the strategy of the Yangtze River economic belt, Wuhan international port as an important hub port in the middle reaches of the Yangtze River has played a more and more important role. By clarifying the evaluation index system of inland port competitiveness and using the principal component analysis method, this paper evaluates the development trend of logistics level of Wuhan international port, and then puts forward the ways of promoting the construction of smart port, optimizing inland port system, developing multimodal transport business of Wuhan international port, and taking advantage of the favorable conditions such as Tianhe Airport regional hub and Hubei International Logistics core hub, integrate the port development with the world transportation logistics system, build an international express logistics network system, comprehensively improve the port operation efficiency, and realize the modernization of port infrastructure and equipment, the intelligent automation of port production and operation, the collaborative integration of port operation organizations, the agility and flexibility of port transportation services, and the objective intelligence of port management decisions. Finally improve the competitiveness of Wuhan international port.

Metropolitan area is a spatial form of urbanization with big cities as the center and 1-hour-commuter circle as the basic scope. Transportation in metropolitan areas has the characteristics of high density, high growth, tidal and centripetal. Based on the mobile signaling data, this paper analyzes the travel characteristics of Xiamen-Zhangzhou-Quanzhou metropolitan area. This area is still in the embryonic and rapid development stage. The coastal area has dense transportation infrastructure, high travel intensity, and the centripetal characteristics of the travel network are obvious. At the same time, the multi center development pattern is gradually emerging. Due to the concentration of population and jobs in Xiamen Island, the pressure of commuter traffic and the shortage of rail transit, the development pattern of public transport guiding the expansion of urban development space has not yet been formed.

The obstacle avoidance behavior of one-way pedestrian flow in straight passage was studied based on controlled experiment. Experimental scenes with the length of 5m and 7m passages were constructed. The results show that: the straight passage can be divided into the front straight area, the avoidance area and the back straight area. Pedestrians walk in a stable straight line in the front straight area, and bypass obstacles in the form of a curve after entering the avoidance area. At this time, pedestrians will slow down slightly in the horizontal direction and accelerate slightly in the vertical direction. There is a triangle in front and behind the obstacle, whose area is related to the shape and scale of the obstacle. Pedestrians will speed up slightly in the start-up phase, and their speed will decrease after bypassing obstacles; The change of velocity in horizontal direction is roughly consistent with that in actual direction. And the change of pedestrian speed mainly comes from the horizontal direction of travel. It is found that the circular obstacle has a stronger guiding effect on pedestrian flow than the strip obstacle.

With the development of LNG (liquefied natural gas) fuel powered vessels, the disadvantages of traditional fuel bunkering methods are prominent. Countries all over the world have launched the research on LNG overwater bunkering technology. LNG overwater bunkering refers to the fuel bunkering operation of LNG fuel powered vessels through LNG bunker vessels at designated anchorages or specific waters along the coast and inland rivers. Compared with the traditional LNG tanker bunkering or shore station bunkering, its operation mode is more convenient, doesn’t occupy wharf resources and has higher bunkering efficiency. However, LNG has special dangers such as low temperature, flammability and explosion. In case of fuel leakage accident during operation, fire or explosion may occur, and the consequences will be unimaginable. Therefore, this paper systematically studies the leakage risk in the process of LNG overwater bunkering operation, and puts forward safety guarantee suggestions to ensure the safety of the operation process.

The Three Gorges Ship Lock is an important facility of the Three Gorges Project, and its safety has become the top priority of the Three Gorges Project. With the continuous development of my country's economy and society, there is still a large gap between the current regulatory system for the passage of ships carrying dangerous goods and the requirements of intrinsic safety management. The hierarchical data model is adopted for a comparative analysis of the existing international conventions related to the carriage of dangerous goods, regulations and specifications for passing lockage of ships with dangerous goods. The shortcomings of existing regulations for the passage of dangerous goods ships are put forward to improve the transport normative system, and provide an effective reference for the management of dangerous cargo ships passing lockage.

The investigation of public transport network (PTN) characteristics is significant for optimizing public transport planning and alleviating traffic congestion. Most of the current researches consider the travel demand from the IC card data or the cellular signaling data (CSD), but a systematic and quantitative comparison between the two types of demands is still lacking. In this paper, a supply-demand matrix approach based on multi-source data is proposed. The supply matrix of PTN is calculated based on the bus GPS data, and the demand matrices are established using the IC card data and CSD, respectively. A practical PTN containing 116 bus lines and 997 stations in the Sanshui district of Foshan is analyzed using the multi-source data for 21 workdays in November 2020. The Sanshui district is divided into 72 regions, and the matrices are matched to them to compare the demand and supply. The characteristics of PTN can be autonomously revealed using the average Euclidean distance and Cosine similarity. The supply and demand imbalances in several regions are autonomously discovered with the analysis results, and the CSD can particularly benefit the discovery of potential travel demand. We believe the proposed approach can provide further directions and suggestions for optimizing PTN.

In this paper, under the influence of the current new corona pneumonia ( 2019 - nCoV ), a prototype system of public emergency command and control service for Beidou's precise new space-time mobile target is proposed. This system uses the Beidou positioning equipment to be embedded in the mobile terminal and further realizes the precise control of the positioning trajectory of logistics vehicles and related personnel through the Beidou new space-time mobile target public emergency command and control service prototype system. At the same time, the grid difference technology is used to improve the positioning accuracy of the moving target so that the unmanned robot in the epidemic area can work more accurately. While reducing the risk of infection, the efficiency of epidemic prevention can be improved through systematic data analysis. The data can be collected through the platform to form an analysis report to provide decision support in the government's epidemic prevention and control work.

In recent years, Mobility as a Service (MaaS) system has been widely used at home and abroad. It integrates various modes of transportation, provides door-to-door travel services for travelers, and advocates people to reduce private cars to expand the proportion of green travel. On this basis, this paper analyzes the possible travel needs of travelers before travel, and proposes an improved genetic algorithm. The initial population generation strategy is improved to avoid loops and invalid paths in the first generation population. The mutation operation strategy is improved, so that the good genes of the father can be retained, and at the same time, the mutation is carried out in the direction of the traveler's needs. Finally, the virtual road network is used to verify the model and algorithm. The results show that the proposed algorithm can calculated the route planning based on travelers' multiple travel demands in the number of iterations rarely.

The identification of dynamic parameters of bridge health monitoring aims to reflect the inherent dynamic characteristics of bridge structure, and is an important part of bridge health monitoring system, which is of great significance to longterm health monitoring and operational safety of bridges. According to incomplete statistics, at present, there are more than 20 public railway bridges with a span greater than or equal to 300m in normal operation in the world. Based on the existing health monitoring technical condition evaluation methods, the analytic hierarchy process (AHP) principle is mostly used to establish the analytic hierarchy process model of monitoring bridges, and the evaluation results of the bottom indicators are analyzed layer by layer and summarized to the top level to complete the evaluation of the technical condition of monitoring bridges. Based on the underlying monitoring data, the dynamic parameter identification technology of bridge health monitoring is studied in this paper. The health monitoring system of bridge structure collects relevant data of the environmental function and dynamic and static response of the test bridge under the related load through a variety of sensors reasonably installed on it, and processes the results of relevant data by means of system identification method and evaluation method, so as to judge the health state of the structure and make the decision of bridge maintenance and repair based on this.

Based on the results of water conservancy census data, this paper makes full use of two-dimensional vector data and shows water conservancy data in one map. It also comprehensively uses geographic information and data service integration to comprehensively manage and use water conservancy data in multiple time, space and regions. The use of Web GIS technology effectively improves the management, statistics and summary of water conservancy census data, and provides standardized, efficient, abundant functions for quickly establishing water conservancy application system. The integration of water conservancy information resources based on one map can improve the application level and management ability of water conservancy data, and meet the function and performance requirements of public service of water conservancy spatial information.

Noise is unwanted sound from environmental sources. Noise exposure has long been recognized as a significant source of health hazards in working life. It is increasingly seen as a commonly harmful environmental factor in cities, directly impacting mental and physical health. This paper intends to present and diagnose the urban noise problem from multiple perspectives through a quantitative study of the noise complaint reports from the 311 system noise complaint platform in New York City, USA in 2020, by conducting correlation analysis and regression analysis on noise formation in terms of community-level characteristics, land use characteristics and the number of public facilities factors. Through the diagnosis of the noise problem in New York City, the findings have a good insight into solving the current issues of noise management in China's urban management: firstly, the legislation on urban noise management needs more precise and more scientific and operational; secondly, the means of urban noise management should promote more diversity; thirdly, the sources of urban noise will be more precisely grasped and controlled; fourthly, the types of urban noise needs more openly public to the public to know the kind.，and more widely known to the public.

In the context of rapid economic and social development, human production activities are also increasing. Intelligent surveying and mapping technology and means have achieved great development. The popularization and application of new surveying and mapping equipment has produced a large number of geospatial data. The traditional static spatial data has been gradually replaced by geospatial big data, and has become an important form of geographic information socialization. The space-time big data and cloud platform of smart city can make the space-time information penetrate into all aspects of urban development and people's life. It is the "cornerstone" of smart city. For government data and personnel, you can provide support for data space, operation data and sensing data, and make use of the space-time big data and big data analysis function of cloud platform to meet the needs of various business departments. This paper adopts the method of association rules. Data mining is a new subject and has broad application prospects. Therefore, it has attracted many scholars to study it. Among them, association rules are the earliest and important field.

High-speed railway subgrade is an important structure to support the dynamic load of train and ensure the safe operation of train. The calculation of subgrade settlement has always been a research hotspot in academic circles. This paper analyses various subgrade settlement calculation methods, explores the applicability of subgrade settlement calculation methods in reducing subgrade settlement design of high-speed railway through comparative analysis.

Traditional courtyard construction not only reflect the plain view of nature, but also well meet the human requirement of comfort. With the help of actual measurement and CFD digital technology, we did research on environment-friendly perspective of Huizhou traditional residential courtyard. We apply ECOTECT simulation software to analyze microenvironment state of different types of Huizhou traditional residential courtyard. The result show that essential factors such as courtyard orientation, enclosure form, spatial layout have significant impact on micro-environment state of traditional residential courtyard. Huizhou traditional residential courtyard have excellent characteristics of defense against the cold wind and keep warm in winter and ventilate and cool down in room in summer. These characteristics show that the courtyard could keep coexist with environment and provide ideas for modern courtyards design.

With the rapid development of information technology, 5G, big data, artificial intelligence, virtual reality and other hightech gradually applied in the field of mining, so that the mode of mine production and management has undergone fundamental changes. In this paper, the paper uses the key words of 5G-based smart mine to carry out the literature analysis from 2008-2021, and further studies the key technologies, the results of which provide the research direction for the subsequent construction of green, intelligent and sustainable intelligent mine.

Tunnel traffic noise prediction is of great significance in traffic noise. However, there is no complete traffic noise prediction standard for highway tunnel at present. This paper intends to study the traffic noise difference between the middle of multi lane tunnel and ordinary pavement through vehicle flow model and long space sound field model. The research shows that the sound pressure level in the middle of tunnel is significantly higher than that of ordinary pavement, and the difference of equivalent sound pressure level of vehicle flow is less than that of ordinary pavement due to reverberation.

Traffic is a dynamic coupled system consisting of four factors: humans, vehicles, roads, and the environment. Safe and controllable external stimuli and the psychological condition of drivers guarantee the safety of vehicle driving, but due to the lack of quantitative means of assessing driver and environmental factors, accident analysis and prediction methods often lack scientificity. This reduces the effectiveness of traffic accident prediction and control. In this study, a full-factor urban traffic accident prediction framework is constructed using real-vehicle test data and open-source data to achieve the accurate prediction of urban traffic accidents. The real-vehicle test data include 1022 sets of experimental data obtained by 23 experimenters for more than 7 consecutive laps on 6 routes with large variability. The wide application of deep learning in computer vision and the popularity of physiological acquisition technology in daily life provide quantitative means for assessing driver and environmental factor variables, and the open-source data include traffic volume data from the drip platform, street view data and road design information. In addition, the analysis methods involving the elasticity coefficient and marginal benefit coefficient are used to analyze the potential connection between correlated variables and traffic safety. Based on this, all-factor traffic safety improvement measures are proposed, providing theoretical support and methodological support for the improvement of traffic safety on urban roads.

Smart city is the trend of urban development in the information age. As a city’s information center, libraries should actively contribute to the construction of smart cities. This study uses Nvivo software to make a qualitative analysis of the smart city implementation plans of 11 Chinese cities. The result shows the development of smart cities includes five core nodes, including smart city governance, smart city government management services, smart information platform construction, information data security, and industrial innovation and development. In view of the text analysis results, this research proposes that in the process of smart city development, the library should become the information center of the city and play an important role in improving the intelligence level of smart city residents.

The advent of Internet of Things and widespread mobile devices in urban cities have motivated a new paradigm emergence that is smart city. Data acquired from ubiquitous devices can be used to train the Artificial Intelligence(AI) models that support the smart services and benefit society in all aspects. Federated learning (FL) as a distributed learning technology enables multiple edge nodes collaboratively train a global model with remaining their raw data in local, which protects data privacy. Previous efforts mostly focus on offline FL task assignment where datasets are offline, i.e., continuously training the model with the same datasets. Actually, there is always new data produced during training process and these new data should be added to training datasets as an update for improving the performance of the model and online datasets scenario is more realistic. Based on Lyapunov optimization theory, we constructe a dynamic queue model to formalize the online dataset of each edge node. To effectively assign the model to the edge nodes, an online task assignment algorithm that is Federated Online Control Algorithm (FedOCA) is proposed. Through empirical analysis, we found that our proposed algorithm can achieve higher accuracy compared to Fedavg on the FashionMNIST dataset. We also verify the effect of batch size on accuracy, and find that the larger batch has worse effect.

Although many technological products for the blind have been created in the intelligent and the digital age, guide dogs are irreplaceable options in supporting blind travel, both bodily and psychologically. However, there are nonetheless some drawbacks in the way guide dogs assist in travel. In order to make up for the shortcomings of guide dogs, optimize the travel experience and ensure the safety of blind people, the smart guide dog harness (“E-guide”) based on image recognition technology, communication technology, GIS positioning technology, etc. was designed. In order to ensure that the design of the smart guide dog harness is practicable and implementable, first, 4 user pain points in the process of guide dog-assisted blind travel are obtained through various research methods. 16 basic requirements of guide dogassisted blind travel based on the user pain points is compiled. Afterwards, a two-dimensional questionnaire based on the “Kano Model” was created based on the above 16 travel requirements, and the blind people assessed their satisfaction based on each travel requirement. The results of the questionnaire were statistically and analytically analyzed according to the two-dimensional attribute classification approach based on “Kano Model” to obtain the requirement attribute for each travel requirement. Then, the Better-Worse analysis was used to transform each requirement attribute into a quantitative requirement index, so as to clarify the travel requirements of guide dog-assisted blind travel that need to be satisfied as a priority, and provide guidance and reference for the design and research of smart guide dog harness. Finally, a simulation experiment was conducted with and without the “E-guide” to assist blind people to travel. The travel period and heart rate changes of blind people traveling were tested. The results showed that “E-guide” can effectively improve the physical and mental satisfaction of guide dogs in assisting blind people to travel.

On the basis of combing the related research of digital twin technology and smart library, this paper puts forward a construction scheme of a new generation of smart library based on digital twin, designs the system framework of digital twin library, and puts forward the bottleneck and coping strategies of the scheme. The construction of a smart library based on digital twins, deeply integrates cloud computing, big data, Internet of things and other technologies, constructs a four-tier architecture system, realizes the storage, calculation, analysis and visualization of library data, and enables the fine management and intelligent decision-making of the library, which is a new idea to promote the construction of a new smart library. It has certain reference value for the research and construction of digital twin library.

As an important part of smart government, smart government interactive platform is a channel for the government to connect and communicate with public opinion. In this paper, based on the research data of wisdom government interactive platform in Henan Province, we use super efficiency DEA and Malmquist index to conduct efficiency analysis on it. The results show that the overall wisdom government interactive platform rises first and then falls, with obvious S-shaped fluctuations, and now shows a stable development. This paper provides suggestions for the government to improve the development of smart government platform from both management and technology aspects, in order to help improve the image of the government and promote the construction of smart city.

Equipment allocation is an important part of the military equipment management. The equipment allocation plan is a guarantee plan for the military to carry out tasks, and its quality directly affects the formation and display of combat effectiveness. In this paper, combined with the characteristics of the supply of equipment allocation, the research situation of equipment allocation decision methods was expounded and the relevant models and algorithms of equipment allocation decision were analyzed, so as to achieve accurate and economic equipment allocation and supply. The scientific and reasonable analysis of the allocation plan is of theoretical and practical significance to provide auxiliary support for the equipment commander to command and make decisions and to support the improvement of the combat effectiveness of the troops.

Electricity, as a secondary energy source, is an important public resource related to national economic and social development. The contradiction between power supply and demand appears under boundary conditions such as load growth, increase in commodity prices, increase in new energy installed capacity, and China's "carbon peak and carbon neutrality". Therefore, establishing a new model of the interconnection of electricity, energy, cities, economy and multiple social entities based on the new power system is conducive to balancing power supply and demand and energy supply and demand, serving social production and residents' lives, and providing the government with historical, immediate and future expected energy economic information, so as to carry out more timely and effective economic regulation. The urban economic and energy interconnection model based on the new power system has two major characteristics:autonomous learning and human-machine interaction.Its future development direction is to integrate economic activities, enhance emergency reserves and establish a good ecological system. The model mainly includes five parts: interaction of learning ability and technological cultivation ability, deep integration of traditional business and new information technology, integration of economic activities and enterprise boundary, energy emergency and reserve regulation, and applied green power ecosystem.

The emergence of connected and automated vehicles (CAVs) shed light on future traffic development. In near future, due to the mix of human driven vehicles (HDVs)and CAVs, the two types of vehicles can be separated by setting up dedicated CAV lanes for autonomous driving, thus ensuring the operational efficiency, traffic safety and the environment-friendly property of CAVs. In freeways with CAV lanes, the merge area formed by the convergence of ramps is the key to ensuring the high speed and stability of CAVs. The design of the acceleration lane length in the merge area is the core of the operation of the entire merge area, however, the traditional method has certain shortcomings due to its reliance on the gap acceptance theory. Recent literature has shown that gap acceptance theory cannot account for practical traffic phenomenon such as active avoidance and forced merging. Firstly, this paper introduces the statistical method of breakdown events and proposes a breakdown event probability model for highway merge areas considering CAV lanes. The relationship between breakdown event probability and the length of the acceleration lane in the merge area is established through the derivation of equations. Then, based on the above BP model, a method to calculate the length of acceleration lanes in merge area is proposed. Considering 13 flow combinations, the variation of probability of breakdown versus acceleration lane length is plotted. Employing the method proposed in this paper, the length of the acceleration lane can be determined when the flow combination and BP are given. The length of the acceleration lane can be determined when the method proposed in this paper is employed, given flow combination and BP. The results of this paper provide a solid theoretical basis for the future CAV lane setting.

Progress management is one of the important contents of power transmission and transformation project management. Under the premise of considering the construction characteristics and progress management needs of power transmission and transformation project, the project progress management link is decomposed based on WBS decomposition model, and optimizing the schedule of each link through differential evolution algorithm, so as to provide reference for improving the progress control efficiency and effect of power transmission and transformation project.

In the smart home scenario, the heterogeneity of IoT devices makes it difficult to discover the potential relationship between devices, and the existing device search or recommendation methods cannot provide the next device used by the user according to the user's device usage order. We propose a next-device prediction method that combines a Natural Language Processing (NLP) language model and BiLSTM. This method extracts the device activity sequence from the IoT device activity log, and selects two embedding methods, Word2Vec for static word embedding and BERT for dynamic word embedding, to represent the correlation of devices. The BiLSTM network is trained to predict the next device a user will use. The experimental results show that, compared with deep learning models such as SPEED-LSTM, CNN-BiLSTM and BiLSTM-ATT, Word2Vec-BiLSTM and BERT-BiLSTM models have better prediction accuracy, precision, recall and F1 evaluation indicators. Effect. The correct rate of using Word2Vec-BiLSTM on the HH101 dataset is 74.86%, and the correct rate of the BERT-BiLSTM model is 77.43%.

With the improvement of the national economy, the power load has increased steadily. In order to meet the growing demand for electricity from the people, grid companies need to continuously invest in expanding the scale of the distribution network and optimizing the structure of the distribution network. This paper constructs a power grid investment benefit decision-making index system after the power transmission and distribution price reform from six aspects: policy indicators, safety indicators, economic indicators, competitive indicators, risk indicators and social indicators. By evaluating the investment benefits of the power grid, it helps the power grid to pay more attention to investment benefits and improve investment capabilities.

Smart city is a developing concept and the product of the development of urban informatization to a certain stage. It is constantly improved with the development of technology, economy and society. With the powerful driving force of new generation information technologies such as big data, cloud computing, Internet of things, geographic information and mobile Internet, develop smart applications and establish a new and sustainable urban development model, so as to outline a blueprint of "smart city" in the future. The construction of intelligent city is a systematic project. The overall planning and design of smart city is to integrate the information elements required for construction objectives, implementation objectives, knowledge system, construction system, technology application and achievement into the overall scheme, which is the construction purpose, objective and implementation strategy of smart city. The overall planning and design of smart city shall ensure the consistency of the overall strategy of urban management and public services with the city, and develop the corresponding business application platform on this basis. Smart city big data analysis platform integrates various government information platforms and smart city application systems based on big data, cloud computing, artificial intelligence, Internet of things and other technologies, eliminates urban information islands, and realizes the interconnection and sharing of government information systems and smart city public data. The platform provides one-stop city level data development, analysis and application platform support, including big data application solutions such as big data storage, computing, security, tools and services. The platform is simple and easy to use. Through XML and web services technology, big data technology, cloud storage technology, UML modelling language, workflow technology, etc., it can quickly realize the in-depth data analysis of city level applications, industries and enterprise applications, discover data laws and predict future trends. It can provide authoritative and reliable public data resource services, spatio-temporal information bearing services, data mining and decision support services for various smart city application systems, enhance the credibility of the government, and provide a reliable support platform for government management, social livelihood, entrepreneurship and innovation.

When the existing residential energy management system is dealing with the calculation of multi-source energy management, it is affected by the system single data linear management strategy, and the multi-source energy information data layer is confused, a multi-source distributed energy real-time management system is designed for the energy saving of intelligent community. The DES or CCHP framework based on distributed multi-source energy management is designed. On the basis of building distributed hardware platform, multi-source management strategy is used to integrate and optimize different types of energy data. In addition, the distributed algorithm is introduced for differential synchronous calculation of integrated energy data to realize data management consistency. Finally, the realtime management effect of data is realized by updating the data time variable. Simulation experiments show that the proposed energy management system has better management efficiency, the best energy saving effect in the process of energy management and better real-time performance.

With the aggravation of aging society and the general trend of home-based elderly care, how to combine community forces to provide all-round protection for the elderly has become an urgent problem to be solved. The system focuses on meeting the diverse needs of the elderly. It is divided into three roles: relatives, the elderly and community administrator. It realizes the functions including health monitoring, meal ordering, entertainment and so on. The system is developed by spring, spring MVC and Mybatis website technology to realize the background management function. The Android system mobile phone is used as the mobile terminal, combined with the sensor function of the mobile phone to identify the falls of the elderly, and uses the smart bracelet to detect the heart rate, so as to provide the basic guarantee for the elderly at home and meet the daily needs of the elderly.

In the road video shooting of unmanned aerial vehicle (UAV), the UAV is in an unconstrained state, and the video picture is jitter and unstable. When tracking multiple vehicles in uav video, identity switching of tracking targets is easy to occur. Based on this, an improved DeepSort vehicle target tracking algorithm based on Yolov5s is proposed. When Yolov5s trains the vehicle detection model, DIOU-NMS is used instead of NMS to remove the redundant target position prediction box. Aiming at the fact that DeepSort pre-trained appearance extraction model did not contain the appearance model of the vehicle, the vehicle appearance model was obtained by using the lightweight ShuffleNet V2 network for vehicle rerecognition training on VeRi data. The improved algorithm is used to evaluate the MOT of UAVDT data sets. The experimental results show that compared with the original algorithm, the tracking identity switching (IDSW) of this experimental method is reduced by 49.1%, MOTA is improved by 3.2% and MOTP is improved by 0.3%.

Two problems exist in the theoretical research on pipeline--soil interaction caused by tunnelling. First, it is difficult for the existing mathematical models to maintain both simplicity and accuracy; second, most studies focus on the vertical pipeline-soil interaction and ignore the horizontal pipeline deformation. Based on a continuum medium model, the pipeline-soil interaction caused by shield tunnelling was simulated to determine both the vertical and horizontal soil displacement fields. The governing equations for both the pipeline deformation function and attenuation function were constructed based on the variation principle. These two functions are coupled and then decoupled by an iterative process. The model has the following advantages: 1. The model has a simple solution form that is convenient for application. 2. The model includes the influence of soil continuity and produces results with a good precision. 3. The proposed model is able to calculate the analytical expression of the soil spring factor and soil shear stiffness factor, making it possible to quantitatively analyze the pipeline--soil interaction. Through comparison with monitoring data, the proposed method was verified. Ultimately, the parametric study shows that large horizontal pipeline deformation may be caused by shield tunnelling, and the influence of soil continuity on pipeline--soil interaction is remarkable.

The integrity of motor vehicle travel trajectory is widely used in macro traffic management, vehicle travel prediction and traffic problem analysis[1]. However, in reality, due to the lack of transportation equipment and the complexity of the road, it is difficult to obtain a complete vehicle travel trajectory. Based on massive bayonet data, aiming at the phenomenon of incomplete vehicle travel trajectory, combined with SUMO (traffic system simulation software) platform, this paper establishes a dynamic routing algorithm model based on Astar [2] and Dijkstra [3], The index data combined with bayonet data is introduced into the model to increase the practicability of the model. Finally, the accuracy of the model is verified through the comparison of actual cases. Provide reliable data support for further research on traffic travel scheme.

The construction of high-rise residential buildings is the result of economic development and scientific and technological progress. Its emergence and development is due to many factors, such as the concentration of urban populations, the lack of land resources, the increased demands of the people for the quality of housing and the need for urban modernization. At the same time, the quality of life and environmental problems of high-end residential residents are also becoming increasingly prominent. In order to make people's living environment more comfortable, this paper conducts research and analysis on the current situation of residents' lives, summarizes the existing problems at this stage, discusses the application of Internet of Things technology to solve many problems related to intelligent buildings, and demonstrates the impact of intelligence on livable buildings through examples, and draws the necessity of intelligent ecological livable buildings.

The metropolitan metro station areas are places where a large number of urban activities take place and gather. Compared with other areas, commerce, business, and public service elements such as culture, medical care, and education are more concentrated than non-station areas, and they are more likely to face the problem of unbalanced development of transportation and land use. The five new towns are the main carriers of the rapid spatial growth of Shanghai. It is useful to find out the problems existing in each station area by measuring the coordinated development level between public transportation and land use in these areas in new towns. And it is also beneficial to put forward improvement measures in the station area and optimize the urban spatial structure. Based on the node-place model, this study takes the metro stations in the five new towns in Shanghai as the research object and constructs a coordinated evaluation index to measure the coordinated development level of rail transit and land use. According to the measurement results, the research stations are divided into four categories: the new town center, community, suburban, and edge type. For each type, the crux of the problem is analyzed and optimization suggestions are provided. The evaluation results may also assist in the guidance for the renewal and construction of the new towns.

In terms of alternative rainwater resource utilization, the utilization of urban rainwater resources is very important. This paper summarizes the history, current situation, and utilization pattern of rainwater resources utilization in Qingyang, a typical city in the Loess Plateau. And on this basis, the main problems of urban rainwater resource utilization are analyzed and a method is proposed to evaluate the potential of urban rainwater resource development and utilization. According to this evaluation, if the precipitation guarantee rate is 50%, the potential of rainwater resource utilization in Qingyang City is 18.72 million m3, while the current utilization of urban rainwater resources only accounts for 12.6% of the total amount available, leaving a large potential for the utilization of rainwater resources in the city. This paper also suggests that groundwater replenishment is the top priority for the sustainable development and utilization of urban rainwater resources in Qingyang.

The detection of the movement of urban tourist groups has been a hot spot in the management of smart city and smart traffic planning. The development of ICT communication technology and its big data information have brought new research perspectives and technical means to this problem. Taking Jinan online travel blog data as an example, combined with social network analysis method, mathematical statistics and GIS spatial analysis methods, this paper calculates the structural parameters such as the density, central potential and centrality of network nodes from the two levels of network and nodes, constructs the tourist flow network diagram in Jinan, and further analyzes the node attributes and network structure system as well as function relationship. The results show that: the distribution of tourist attractions in Jinan is extremely uneven, and there is a phenomenon of “cluster” of attractions, forming an aggregation distribution trend centered around Qianfo Mountain as a whole; the tourism nodes have significant characteristics of hierarchical differentiation. The role of nodes in the network has led to an obvious trend of network centralization, among which the core nodes have a high degree of control over the network; and the structure of tourist flow network in Jinan is unbalanced, with Baotu Spring, Daming Lake and Quancheng Square having higher network connectivity but lower overall network density. The research based on the background of big data reveals the mobile network structure characteristics of urban smart tourism crowd, which might provide a direct scientific decision-making basis for urban smart management and smart traffic planning.

In recent years, many cities in China and abroad have put forward the concept of "Building a smart city" in urban construction. In order to meet the power demand of smart city, modern distribution network planning is a key element in the development of smart city. Based on this, this paper first analyses the configuration requirements of distribution network planning in the urban construction of smart city, then describes the current situation and problems of power grid planning, and finally puts forward the corresponding improvement countermeasures, in order to provide reference for the follow-up research in this field.

At present, the shortage of parking resources, the demand continues to increase, the increase of the contradiction between supply and demand of parking is the urbanization problem that all countries are facing, especially the mismatch between supply and demand of parking in residential areas leads to the scramble for parking resources, illegal parking and other chaos, is becoming an important challenge of urban management. In order to cope with such challenges, all countries are actively looking for solutions, but based on different administrative management modes, governments have different administrative methods and means. Based on the detailed analysis of China's engineering experience, this paper aims to provide reference for other countries and regions in alleviating urban parking problems through two effective promotion modes that are livelihood oriented and government oriented.

Based on the theory of visual perception, this paper makes a quantitative evaluation and Analysis on the urban skyline of Macao by using mathematical quantitative method. With the help of ArcGIS and AutoCAD software, this paper makes a quantitative evaluation on the contour tortuosity, spatial hierarchy and the number of architectural turning points of the urban skyline. The research obtains the advantages and disadvantages of Macao's urban skyline from different perspectives and puts forward some suggestions for future development.

In order to study the effect of melting ice and the mechanical response of the pavement on the Conductive Ultra-Thin Anti-Skidding Wearing Course (CUAWC) under different ambient temperature, ice thickness and input power. Firstly, epoxy resin is used as the bonding material, graphite and carbon fiber are used as the conductive material to prepare the CUAWC. The results show that the input power dominates the melting effect of the CUAWC, followed by the ambient temperature and the thickness of the ice layer. Then using ABAQUS for finite element modeling, the road surface mechanical response analysis of the CUAWC under the conditions of fixed input power, ambient temperature and ice thickness is simulated. The results show that under the no-loading effect, the temperature stress generated by the structural load-bearing layer of CUAWC during the process of melting and snowing does not have much influence on the structure of the pavement.

In 2020, the FMCG market suffered a severe impact due to the COVID-19 pandemic. The price of FMCG fell for the first time in five years as consumers turned to buy cheaper commodities because of the uncertainty. However, the overall sales growth of FMCG remained at a high level. It indicates that the FMCG enterprises are supplying rising demand at decreasing prices, which results in lower profits. In addition, due to the rising price of raw materials, further reducing the profits of FMCG enterprises. In view of the problems above, reducing cost has become the primary issue considered by the FMCG enterprises. Therefore, this paper proposes a mode of cross-level service to optimize the FMCG supply chain network in view of the long distribution channel chain of FMCG, builds a model of RDCs location and capacity design under the mode of crosslevel service, and obtains the optimal solution by Supply Chain Guru.

The antenna part, the transmitting part and the receiving part in the signal transmission of the radar system are studied and designed in detail. In order to achieve antenna polarization and target high resolution, the antenna array and simulation are designed in detail. In the transmitting design part, the PLL+VCO scheme is adopted and the advantages of the solid-state transmitter are analyzed. According to the existing domestic research, the receiving and processing part is studied in detail, and the signal transmission of the radar system is realized.

To simulate the durability of iron tailings asphalt mixture under high temperature and rainy environment, Hamburg wheel tracking test is used to examine the impact of different asphalt mixture types, iron tailings content, asphalt content, and lime content on the durability of iron tailings asphalt mixture in a hot and wet climate. The results show that the type of mixture, the number of iron tailings, amount of asphalt, and the amount of lime have significant effects on the loading times, wheel rut depth and total deformation rate（Dr） of the iron tailings asphalt mixture, and the amount of iron tailings have a significant impact on durability. The most significant impact on performance occurs when the amount of iron tailings exceeds 15% and the amount of lime is less than 1.5 percent; the mixture's durability is significantly reduced; it is recommended that the iron tailings asphalt mixture be designed for durability in harsh environments Inspection.

This paper proposes a new model of optimal combination scheduling, which has a background of the spread of highquality public transport. Considering passengers’ willingness to have a seat on the bus, we design a bus line with two kinds of bus types; one is the regular buses with few seats and flat fare, the other is the VIP buses with enough seats for everyone and a higher fare. An optimization model is formulated based on a two-party game (involving the transit enterprise and the passenger) to determine the optimal combination bus schedule of regular bus and VIP bus. The nondominated sorting genetic algorithm-II (NSGA-II) is adopted to solve the model. With numerical experiments, we demonstrate the feasibility of the mathematical model.

Stochastic evaluation of traction load of electrified railway is always a difficult problem in power supply calculation of electrified railway. The traditional analytical model is difficult to describe the random fluctuation in the operation process of electrified railway and lacks effective system nonlinear and non-ideal factor modeling methods, so it cannot obtain reliable dynamic simulation results of electrified railway traction load. In this paper, the key influencing factors of electrified railway traction load characteristics are defined as independent random variables and a random probability model is constructed from a statistical point of view. Using the existing measured data, the dynamic model of traction load probability including the influence of random factors is obtained through parameter identification and the results show that the model error meets the needs of practical engineering. The practical application example of the model in the operation scenario is given, which shows that the model can be well integrated into the existing power supply simulation system.

Mobile source pollution has become an important source of air pollution in large and medium cities, and an important cause of fine particulate matter and photochemical smog pollution. There is an urgent need for suitable and effective emissions prediction tools in both scientific research and industry. In recent years, deep learning has outperformed traditional models in many machine learning tasks as the size and dimensionality of data volumes have increased. Many deep neural network models have been successfully applied to solve microscopic and macroscopic emissions modeling. In this paper, we provide a comprehensive review of recent work on mobile source emissions prediction using deep learning methods. Finally, we provide a deeper discussion of the future prospects and ongoing challenges.

Biofuel is a kind of new energy source which has the advantage of traditional fossil fuels over environment protection issues. It can be produced from plant oils and animal fats, and it produces less greenhouse gases like carbon dioxide. In recent years the production technology of biofuel has been well developed, both the production and the demand rise every year. Since it will be widely used, a complete logistics system should be developed to solve the transportation issues. Vehicle routing problem a.k.a. VRP is one of the transportation problems, it refers to a kind of address problems, the goal of VRP is to figure out the best location of some entities of the logistics system such as the producer, deliver center etc.to minimum the transportation costs. A kind of mathematical models can solve VRP, such as Cluster-First Route-Second Method, Saving algorithm and so on. To build up a complete logistics system for biofuel, they are Indispensable. This paper will show a typical VRP in biofuel logistics system, it will analyze a sample of the Indonesia biodiesel logistics line to figure out the best address of CPO suppliers to satisfied the delivery demand while minimum the transportation cost, and use saving matrix algorithm to solve it and analyze the result.

Rural settlements contain rich regional cultural factors and high-quality landscape style and form, which is the essence of China's agricultural civilization. Taking 537 traditional villages in Shandong Province as the research object, this paper systematically analyzes the spatial distribution pattern and influencing factors of traditional villages in Shandong Province by using the methods of GIS, RS and mathematical statistics. The research shows that the traditional villages in Shandong Province are obviously concentrated in space, forming two concentration centers in the mountainous area of central and southern Shandong and the hilly area of eastern Shandong; Traditional villages are concentrated in piedmont/intermountain plain, hills and low mountains. The number of villages varies greatly in different terrain areas. The number of villages is negatively correlated with elevation and slope, and the number of villages is large in plain areas; The distribution of traditional villages has a significant positive correlation with altitude, and the positive characteristics are significant. Traditional villages are mainly concentrated in the sunny slope; Traditional villages are far away from the water area as a whole and are not highly dependent on water sources. The study can provide guidance for the protection and sustainable development of traditional villages in Shandong Province.

In order to explore the impact of automotive technology on the highway and railway freight transportation industry, firstly, the cost of highway freight transportation based on autonomous driving technology is analyzed. Secondly, from the perspective of market demand, the freight transportation demand is divided into time height sensitive, medium sensitive and insensitivity according to time sensitivity. Transportation costs, transportation time, reliability, convenience, safety and environmental protection are selected as index. The indicators are comprehensively empowered to build a comparative advantage model for railway and highway freight transportation based on automotive technology. The results show that in the time-sensitive and time-medium sensitive freight demand subject, highway transport based on autonomous driving technology has obvious advantages, but in the time-insensitive subject, its comparative advantage is not obvious. It proves that highway freight transportation based on automotive technology has considerable market prospects. This achievement has certain guiding significance for the commercialization of Automotive technology in the highway freight transportation industry, and can also provide reference for the optimization of future freight transportation structure in China.

In order to solve traffic accidents and traffic congestion, an electromagnetic radar system suitable for smart cities is designed. The key of electromagnetic radar is to realize the radiation and collection of ultra-wideband step-frequency continuous wave signal. The time-division transmitter generates an ultra-wideband step-frequency continuous wave signal, which enters into multiple transmitting antennas to radiate in time-division through the switch control signal, and provides local oscillator signals for the multi-channel receiver at the same time. Signal processing is carried out according to the radar algorithm, and the processing results are input into the display control system for display.

Logistics efficiency is an economic index, which can reflect the development stage of logistics. Through comparative analysis of logistics efficiency data of 14 provinces in 5 years(2017-2019), we analyze this. This paper uses three - stage model to analyze logistics data of the 14 provinces in 2019 which is based on building a model includes the relative input factors and output factors in this paper. In addition, the low logistics efficiency caused by low management efficiency, environmental noise and input redundancy is analyzed by using SFA model. Then uses the ANN network model to analyze the improvement of logistics efficiency in each region. The outcome show that some provinces’ logistic efficiency needs to be improved. Some input factors need to be adjusted like logistics technology investment, logistics transport volume, management investment, scale of logistics labor.

Most gas leakage traceability methods are unsuited to the subway platform environment. A method for tracing the sources of hazardous gases in the subway platform environment is proposed. A sample set of simulated sources is constructed through the simulation of hazardous gas diffusion. Field monitoring data is matched with all simulated source samples to identify monitoring response time, suspected sources, and suspected areas. A diffusion simulation sample set composed of 435 simulation sources and 9 test sources was constructed, and the influence of time registration accuracy and the number of sensors on the traceability results was analyzed. Results show that the positioning error (the distance between the suspected source and the test source) increases with the time registration error. More sensors mean a smaller positioning error and shorter response time. Considering the positioning error and the decreasing trend of response time and operation and maintenance costs, installing 4 sensors is cost-effective. The research results can provide reference for the prevention and control of dangerous gas leakage in subway stations.

The main purpose of this study is to analyze the side slip of vehicles on freeway under cross wind, and establish a calculation method of safe driving speed of freeway vehicles under cross wind. The vehicle dynamics model is used to analyze the side slip condition of vehicles under the cross wind condition of freeway, and the safe driving speed is studied on this basis. Firstly, based on the comprehensive consideration of cross wind speed, vehicle type, road condition and vehicle speed, the driving stability of four typical vehicles in China is analyzed; Then, the safe driving speeds of different types of vehicles under different cross wind speeds are calculated. The results show that under the action of cross wind, the greater the vehicle speed is, the greater the risk of side slip is. On the freeway, an appropriate cross wind speed limit is needed to ensure the driving safety under cross wind conditions.

Due to the particularity of oil tankers and the cargo on them, accidents such as fires and explosions are prone to occur during transportation and operation, leading to potential risks that cannot be ignored in terms of life, economic property, and the environment. To reduce the risk of the waiting process of inland water tankers before passing the lockage and ensure the tankers' safe transportation in the inland river, this paper analyzed the collision-leak-explosion problem of the tankers. Based on the hazard and operational analysis method (HAZOP), this paper further integrated the layer of protection analysis method (LOPA) to identify and evaluate the risk of oil tankers crossing the lockage in the inland river, and corresponding suggestions were given.

As one of the main energy sources in China, coal is an important foundation of the national economy and the main source of power for modern production. However, the mining and utilization of coal has caused immeasurable damage to the ecological environment for a long time. In the current era of carbon emission reduction, it is urgent to build a coal green logistics system, and how to evaluate the coal green logistics system is the cornerstone of the system's establishment and improvement. According to the process of coal production and sales, this paper establishes the evaluation index system of coal green logistics system, selects a specific enterprise as an example to verify the validity and reliability of the evaluation system, so as to provide a reference for coal enterprises to implement green logistics.

Delineating restricted areas or roads against vehicles has been a widely used method to reduce the contribution of heavyduty trucks to pollutants such as nitrogen oxides and particle matter (PM) in cities. However, the improvement of traffic restriction on air quality is rarely studied through real monitoring. By investigating the variations of air quality at the roadside and national monitoring sites, this study investigates the impact of the restriction against heavy-duty trucks on the air quality around a typical port transportation corridor. During the restricted period, the average hourly traffic volume of trucks was decreased by 88.6%. For the pollutants near the roadside, the average hourly particle number (PN) concentrations of PN2.5 and PN10 were both reduced by 43.4%, and the average hourly mass concentrations of PM2.5, PM10, nitric oxide (NO), nitrogen dioxide (NO2), and sulfur dioxide (SO2) were decreased by 16.4%, 31.5%, 50.6%, 11.6%, and 22.2%, respectively. For the pollutants at the national monitoring point, the average hourly mass concentrations of PM2.5, PM10, NO, NO2, and SO2 in the downwind direction were decreased by 64.8%, 60.3%, 63.8%, 27.6%, and 28.6%, respectively. Obviously, the restriction of heavy-duty trucks can effectively improve the air quality along and around the arterial road.

Air springs have been widely used in suspension systems of vehicles. While for the vehicles that do not have air suspension system in the original design, it is often of high cost to refit them with air suspension. In this paper, a vibration isolation platform based on air spring is designed, which can achieve low lost portable air suspension without refitting the vehicle. Simulation model is established and some simulation work has been conducted to explore the overall characteristics of the system. Simulation results show that the system is perfect for the vibration isolation of environment vibration frequency larger than 2 Hz, especially larger than 5 Hz. The design and simulation in this paper gives an alternative that can realize portable air spring based vibration isolation for fragile objects without refitting vehicles that have no air suspension.

In the road video shooting of unmanned aerial vehicle (UAV), the UAV is in an unconstrained state, and the video picture is jitter and unstable. When tracking multiple vehicles in uav video, identity switching of tracking targets is easy to occur. Based on this, an improved DeepSort vehicle target tracking algorithm based on Yolov5s is proposed. When Yolov5s trains the vehicle detection model, DIOU-NMS is used instead of NMS to remove the redundant target position prediction box. Aiming at the fact that DeepSort pre-trained appearance extraction model did not contain the appearance model of the vehicle, the vehicle appearance model was obtained by using the lightweight ShuffleNet V2 network for vehicle rerecognition training on VeRi data. The improved algorithm is used to evaluate the MOT of UAVDT data sets. The experimental results show that compared with the original algorithm, the tracking identity switching (IDSW) of this experimental method is reduced by 49.1%, MOTA is improved by 3.2% and MOTP is improved by 0.3%.

In order to solve the problem of vehicle congestion in smart cities, this paper proposes a new network model structure (VGG8-1-CapsNet) to classify the types of vehicles. First, the first 8 convolutional layers of VGG16 and one convolutional layer are combined to form the feature extraction layer of the network model. Secondly, the obtained features are input into the capsule network, and the three-dimensional spatial feature conversion is performed on the extracted features. Finally, the dynamic routing algorithm is used to output, so as to achieve the purpose of vehicle classification. The experiment-al results show that the model has 98.98% accuracy on the expanded BIT-Vehicle, and the training speed is faster.

With the increasing scale of urban rail network operation, the network level passenger flow prediction is more valuable than single station research. In this paper, we propose an RS-Conv1dGRU-based short-term passenger flow forecasting model for urban railways. The forecasting process consists of two stages: the first stage: considering the spatial dependency between neighboring stations, distant stations with similar functions and accessible stations, we propose the SR-GA adaptive station arrangement method to rearrange the line stations in order to effectively explore the spatial correlation between stations; the second stage :An end-to-end prediction framework based on GRU and Conv1d is constructed to use the stations data from the first stage as input to achieve inbound passenger flow prediction at the network level. The validity of the model is verified by using AFC data of a city metro, and the results show that RSConv1dGRU (using station location rearrangement) shows better prediction results than Conv1d-GRU (considering only geographic proximity), and the prediction effect is improved more significantly during peak hours. Compared with the existing methods, the prediction accuracy of RS-Conv1dGRU is better, where MAE and RMSE are 10.45 and 18.10, respectively.

According to the characteristics of maglev trains, technology like fiber grating speed measurement, eddy current speed measurement, Doppler radar speed measurement are selected, which are suitable for the complex magnetic field environment and are used for maglev train speed measurement. According to different technical characteristics, a variety of sensor fusion speed measurement methods and equipment layout schemes are studied. Accurate speed measurement, zero-speed detection of maglev trains are realized. The speed measurement of the fusion of multiple speed sensors can help to achieve precise train control, zero speed determination and precise parking.

As the ratio of the actual number of parked vehicles to the number of parking spaces, the parking lots saturation degree of new-type service area is not only related to the travel experience of drivers and passengers, but also affects the safety and operation efficiency of new-type service areas. However, the current studies do not directly reflect the operation of vehicles in parking lots at different levels of supply and demand, and are rarely directly applied to the design and construction of new-type service areas. In order to study the effect of parking lot saturation degree on vehicle driving in new-type service areas, and apply the research findings to the planning and construction of new-type service areas, considering the dynamic and real-time characteristics of saturation degree, parking lot models of new-type service areas are established by means of simulation modeling relying on VISSIM traffic simulation platform. Combined with the field research results of newtype service areas, delay time and travel time of vehicles are selected as indicators to reflect the degree of mutual interference between vehicles, and the relationship between saturation degree and mutual interference between vehicles in parking lots is clarified. The results show that the degree of mutual interference between vehicles is gradually significant with the increase of saturation degree, and the more parking spaces share a transfer lane, the more obvious the influence of saturation degree on mutual interference between vehicles. When the saturation degree exceeds 80%, the interference between vehicles becomes serious and some vehicles entering parking lots cannot find parking spaces. It is suggested that the saturation degree should not exceed 80% when determining the scale of new-type service areas. At the same time, in the planning and construction of new-type service areas, it should avoid sharing one transfer lane with too many parking spaces, so as to reduce mutual interference between vehicles.

Accessibility is an important indicator for smart city development. The high accessibility performance makes any form of transportation system generally accepted and actively adopted by travelers. However, known as a crucial element in coordinating the transportation and land use, most research does not consider the road accessibility and its interactive relationship between spatial factors at block level. Taking Algiers as a case study, this research characterized urban morphology in six accessibility types. The result indicates single frontage with interval accounts for over half of the main urban district (48.7%), while the single frontage with lane accounts for the smallest portion (4.2%). Double frontage and single frontage are likely to be the ideal apparatus for smart city construction at block level. New blocks may mostly follow the types of single frontage with interval and direct access with limited interior circulation as a method to meet sustainability standards. This paper provides an innovative method in investigating dynamics of existing urban transportation.

Aiming at safety improvement of a hub interchange ring ramp in use, the existing factors which infects traffic safety will be analyzed. Which are identified by road alignment, such as turning radius, sight distance and curve superelevation. The road technical conditions and the vehicle speed data will be obtained through radar and field investigation. In addition with the traffic accident analysis,the modeling and simulation in TruckSim, the main reasons for accidents will be figured .Therefore, provide strong technical support for future traffic safety improvement.

The adjustment of train operation is the core issue of train dispatching and commanding. The train operation runs in the predetermined sequence, and the orderly operation sequence is the key to the safety, efficiency and punctuality of the train. However, during the actual operation of the train, the train may be delayed due to equipment failure, extreme weather or human-induced deviation of the train operation from the plan. In order to ensure that the train operation returns to normal as soon as possible, the train operation may be adjusted globally. Based on the big data of train operation, this paper builds an intelligent prediction model for train operation adjustment, and predicts whether the train needs to overrun and other adjustments. It has been verified that the prediction model can achieve a good prediction effect. Model realization The big data based on scheduling experience provides scheduling decision assistance for schedulers, which is the basis for the realization of intelligent scheduling.

The high-speed railway is a kind of transportation with high speed and large volume, usually used for passenger transport. The high-speed railway system plays a dominant role in the railway system in China. In this paper, the planning of a high-speed railway network in China is introduced, and a specific line, which is the Beijing-Shanghai highspeed railway line, is discussed. This paper also analyzes the structures and costing of stations along the Beijing- Shanghai high-speed railway line.

In recent years, due to the rapid increase in private car ownership in China, the number of people traveling by car has doubled. This has also greatly increased the market demand for self-driving campsites and the rapid rise of the industry but the development of self-driving campsites has not as expected. Therefore, the author conducted field research and analysis on Shaanxi, Gansu, Ningxia, Qinghai, and Xinjiang along the Silk Road by reading and browsing a large number of documents and tourism websites. Among them, the most distinctive Xinjiang region is selected as the research object of this article, focusing on the preliminary construction of the factors that affecting the tourist experience of Xinjiang self-driving campsites. At the same time, the questionnaire was revised, designed and distributed to relevant experts, tourists and industry operators. SPSS23.0 software was used to perform factor analysis on the collected data. After the analysis, it is concluded that the main influencing factors and the level of influence on the experience of self-driving campsites which provides a favorable implementation basis and theoretical foundation for the reasonable developing and planning of the construction of self-driving campsites in Xinjiang.

Existing climbing operation platforms for pylon column construction of long-span concrete bridges are less automatic, time-consuming, and lack effective, centralized, and intelligent safety parameter monitoring devices. In order to study the intelligent safety control systems for the hydraulic climbing formwork of long-span bridge pylons, this paper, taking the Beikou Bridge South Pylon Construction Project as an example, conducts the automatic control research of the hydraulic climbing formwork. Considering the low climbing efficiency of the traditional climbing formwork, great shakes during climbing operations, and poor safety experience, it also proposes an intelligent upgrade of the hydraulic climbing formwork. The proposed multi-point hydraulic synchronous self-adaptive control system, visual monitoring, and wireless communication technologies decrease the single climbing time by 60% and the labor force by 50%, achieving the safety and efficiency of main pylon construction of long-span bridges and providing intelligent technical support and construction experience for subsequent projects of similar nature.

Historic conservation area normally contains land with complex-use types, development and construction activities are restricted by the landscape protection policies. How to coordinate between protection of the historical landscape pattern and solution of the parking problem is one of the key issues. This study takes Langzhong ancient city as an example, analyzing the unique characteristics of parking problems in historic conservation areas, establishing parking demand and supply forecasting model, proposing improvement measures and Strategies based on traffic capacity under the background of resource constraints, which can be used to provide reference for solving the parking problem in historic conservation areas, guide and assist the research, decision-making and management of static traffic system improvement in historic conservation areas in the future.

The new corona pneumonia (COVID-19) epidemic is still spreading globally. The critical role of ports in the global economy and logistics system are highlighted. More and more attention is paid to port development trend. Therefore, it is very important to establish a model to forecast the development trend of the port container throughput. This paper quantified the factors affecting container throughput such as economy and foreign trade, and predicted the container throughput of ports in China. In this paper, a multi-factor dynamic model is constructed, which considers macroeconomic growth, foreign trade import and export volume, containerization rate, single container weight, empty and heavy container ratio and other factors. With the data of 2020 as the benchmark, it is comprehensively predicted that by 2025. China's port container throughput will reach 320 million TEU. The container throughput growth will continue to decline. The average annual growth will be 4.0% in the 14th Five-Year Plan period. Further, this model can be used to predict the development trend of port container in 2050. At the same time, the development peak of port container throughput in China can also be analyzed. This conclusion can provide a basis for government departments and enterprises to make decisions.

In order to improve the effects of High Occupancy Vehicle (HOV) lanes, we propose a scheme that allowing a proportion solo-driving vehicles to use HOV lanes. We use a system optimal model to describe the scheme on a long distance single link with a GP (general purpose) lane and a HOV lane. Then we applied the model to a numerical example to test the application. By analysis of the model, we found the relationship between the carpooling cost and operating cost, and the relationship between the capacity of GP lane and HOV lane in the case of system optimal when the proportion is 1 and 0. The results of the numerical example show the scheme is valid in reducing total travel cost, although might not by encouraging carpooling. And the carpooling cost and the occupancy, etc., are the key to consider when implementing this scheme.

Currently, the number of motor vehicles in the city continues to increase, and large parking lots have become the main space for parking. One of the challenges of parking space navigation planning is to efficiently and conveniently park the vehicle in a specific parking space in a short time. In addition, the factors that need to be considered in the process of parking space navigation have increased, such as multiple exits, entrances, and multiple floors. In this paper, based on AI planning technology, we model the Parking Space Navigation in Multi-Story Car Parking Lot as a standard planning task and use PDDL to construct the domain modelling. Then a state-of-the-art planner is employed to solve the generated planning task. The plan solution of the parking task can be used to guide the car drivers to park their vehicles to suitable or specified locations. Experiment shows that the method in this paper can precisely describe the parking space navigation problem and give high-quality instruction to help drivers park their vehicles.

With the rapid development of aviation business in the world, the number of domestic hangar construction increases year by year. The related hangar engineering basically adopts the integral lifting construction, and its hydraulic integral lifting construction technology has been mature in domestic hangar projects. The concrete column top hoisting measures and synchronous hoisting control are the key technologies for the overall hoisting of steel grid, and they are also the key research objects. The lifting platform is set on the top of the concrete columns of the original structure, temporary lifting ball joints or temporary strengthening box joints are set on the lower strings of the grid frame and truss, and the upper and lower lifting points are connected by steel strand wires. The steel structure of the hangar hall adopts the construction idea of "in-situ assembly on the ground, overall lifting at the stage, and supplementary installation in the air". It greatly reduces the input of resources and ensures that the grid can complete the installation work safely and stably in a short time.

During the "13th Five-Year Plan" period, Ningbo Zhoushan Port's container sea-rail combined transport volume exceeded 1.0 million TEU, but the overall growth rate has slowed down. This paper uses the combined forecasting method to forecast container sea-rail intermodal transport market of Ningbo Zhoushan Port during the "14th Five-Year Plan" period, proposing suggestions on the software and hardware construction based on the prediction results so as to guide Ningbo Zhoushan Port in the next five years with sustainable development of sea-rail united transport.

In view of the low proportion of China's Container Rail-water intermodal transportation, this paper deeply analyzes the proportion index of Container Rail-water intermodal transportation from the aspects of data statistical caliber, transportation structure, transportation distance, transportation price, road network density and mileage, average railway load and railway transportation speed between China and America, and evaluates the real level of China's Port Container Rail-water intermodal transportation.

With the in-depth implementation of China's clean energy strategy the scale of natural gas consumption in China continues to expand and the contradiction between natural gas supply and demand continues to intensify, the development of LNG tank container multimodal transportation becomes an important goal for the industry development. In order to balance transportation safety and economic efficiency, this paper quantifies transportation risks by the mutation level method, constructs an LNG tank container multimodal transportation path optimization model with the lowest transportation cost and the lowest transportation risk as the goal, solves the mathematical model by genetic algorithm, and conducts case verification and analysis. The results show that LNG tank container multimodal transportation has obvious advantages compared with single transportation mode.

Metro network provides mobility to residents and relieves traffic congestion, playing a vital role in the city’s operation. However, due to human faults and equipment failures, the metro network’s functionality and performance will be degraded to a lower level. Therefore, it is necessary to make a robustness assessment for making a safe and reliable metro system. In this paper, we choose Beijing’s metro network as an example to make a robustness assessment based on complex network theory and network science. A random attack and a variety of malicious attacks are imposed on the metro network. The numerical results show that Beijing metro network performs high robustness under random attacks but relatively low robustness under malicious attacks. The proposed method can be easily modified and applied in other metro systems for robustness assessment and enhancement.

Pedal motorcycles are a frequently used mode of transportation on China's roads, and there are increasing traffic safety issues associated with them. China New Car Assessment Protocol (C-NCAP) version 2021 introduces active safety test scenarios for pedal motorcycles. The soft targets used in current active safety test scenarios are mainly referenced to European standards. According to the survey, the characteristics of pedal motorcycles in China are significantly different from those of other countries, so a research on soft targets of scooters based on the characteristics of traffic accidents in China was carried out. This paper details the development process of the target. A detailed study was conducted in terms of traffic accident analysis, scooter size market survey, and test scenario setting.

In recent years, the total emission brought by urban transportation vehicles has been rising. To achieve the sustainable development goal proposed by the United Nations, it is necessary to promote the development of electric shuttle buses in the tourist cities. To minimize the total energy consuming and meet the travel needs of tourists, this paper establishes a mixed-integer linear programming model for optimal electric shuttle bus route design with time windows constraints. In addition, some operational constraints of service characteristics and electric shuttle bus route properties are considered. A heuristic-based genetic algorithm is proposed to solve the established model. The proposed model and algorithm are performed in a test network, and the numerical results show that a near-optimal solution can be obtained, which reduces the total generalized cost. The solutions can provide a theoretical basis for electric shuttle bus route design of tourist cities.

China, as a country with a large number of cars, has complicated road traffic conditions, which makes drivers vulnerable to various factors to induce "road rage" and make dangerous driving behaviors. To solve this problem, we have developed a non-contact vital sign signal monitoring device based on millimeter wave radar, which is used to detect the anger of drivers in real time during driving. In terms of algorithm, we use band-pass filter to reduce noise and separate the driver's chest vibration signal, and get the respiratory and heartbeat signals. Taking them as inputs, the GBDT model is trained, and the fitting analysis of the driver's anger arousal degree shows that the prediction accuracy of the model reaches 92.83%.

In recent years, the situation of new tunnels crossing the existing expressway is increasing day by day. The construction stability and subgrade settlement safety of new tunnels crossing the existing expressway are often the key problems in design and construction. By means of three-dimensional numerical simulation, the safety analysis of construction mechanical characteristics of the new Dananshan tunnel crossing the existing expressway and the safety analysis of subgrade settlement caused by the construction of the new tunnel crossing the existing expressway are carried out. The research shows that the maximum vertical displacement of surrounding rock occurs after the completion of secondary lining construction, which is + 12.75mm / - 15.18mm, and the maximum horizontal displacement of surrounding rock occurs after the completion of secondary lining construction of right tunnel, which is + 10.93mm / - 9.61mm, which is less than UN / 3 = 26.7 ~ 40mm, meeting the specification requirements; Through the analysis of the surface settlement of the transverse and longitudinal sections, the maximum settlement occurs on the surface of the top of the tunnel vault respectively, and the maximum surface settlement of the left and right tunnels are 2.93mm and 3.09mm respectively, which is far less than the subgrade settlement reference value adopted in the specification and this paper.

In the prefabricated construction of bridges, prefabricated concrete segmental box girders and steel-concrete composite girders, which are representative advanced prefabricated structures, have become the primary development direction at present. Prefabricated bridge piers have been initially applied in China, with difficulties in the seismic performance of prefabricated bridge pier nodes and the installation process of segmental prefabricated bridge piers. Meanwhile, the traditional installation method can hardly take full advantage of prefabricated structures, so it is urgent to study intelligent integrated construction technologies. Under the engineering background of the east overpass project in Yangang, Shenzhen, the intelligent integrated bridge construction technology with both main girder and pier column prefabricated was investigated in this study. Moreover, a piece of new-type equipment suitable for the aforementioned intelligent integrated structural installation was developed. On this basis, the intelligent integrated installation of this fully prefabricated bridge was realized.

In the structural system of segmental precast box girder bridge, partial rigid frame system and full rigid frame system have their own advantages and disadvantages. In this paper, based on the existing highway bridge project, the adaptability of the two structural systems is compared in terms of durability in operation period, visual effect, construction period, construction difficulty and cost. The results show that the full rigid frame system has the advantages in durability in operation period, construction period and construction difficulty compared with partial rigid frame systems. Therefore, it is recommended to give priority to the full rigid frame structure system. When conditions are limited, partial rigid frame systems can be used as supplements.

The rapid increase in the number of novice drivers has created serious traffic safety problems. Compared to experienced drivers, novice drivers are more likely to be involved in accidents. The study of the accident characteristics of novice drivers is of great importance for novice driver safety training and accident prevention. This paper analyses the traffic accident characteristics of novice drivers by mining traffic accident data, explores the accident scenarios in which novice drivers are involved in traffic accidents, and filters out the scenarios that are most likely to lead to accidents involving novice drivers according to the random forest algorithm. The study provides theoretical support for the selection of intervention scenarios in further novice driver risk perception intervention studies and has important implications for novice driver crash prevention.

This paper studies the construction of a green, environmentally friendly, scientific and efficient port transportation scheme while meeting the transportation tasks of cargo owners. It makes decisions on transportation routes, cargo volume distribution, and transfer node selection. At the same time, carbon emissions are converted into environmental costs. Considering carbon tax policy and The relationship between the collection and distribution network is analyzed, and the changes of the collection and distribution network under the introduction of the carbon tax policy are analyzed. The results show that the increase of carbon tax has a downward trend in carbon emissions. The carbon tax can be reasonably set according to this law, which can greatly improve the level of multimodal transport, coordinate port benefits and ecological environment, and promote the sustainable development of port collection and distribution.

More and more precast utility tunnels with large cross-sections and complicated structural styles have been built with the blowout growth of utility tunnels in China and its vigorous advocacy of "green building". The precast segmental construction technology of underground utility tunnels has incomparable advantages compared with conventional utility tunnels. This paper introduces a piece of smart construction equipment for precast tunnels which mainly includes five main structures - excavation and support cabin, segment assembly cabin, backfill support cabin, roof platform, and gantry crane, seven systems - thrusting system, articulated steering system, clamping system, grouting system, articulated sealing system, tail sealing system and monitoring system and other supporting systems. The finite element models of excavation and support and segment assembly cabins are established. It is verified that no part of the equipment exceeds the yield strength of Q345 and that the stress and strain are within the allowable range. This paper provides a reference for the smart construction of urban underground utility tunnels.

This paper focuses on a minimum cost route planning problem for electric vehicles that takes into account the customer service time window and midway charging stations as constraints. The objective function consists of the maintenance cost, power consumption, fixed cost, and midway charging of electric vehicles. An integer constraint model is established to solve the lowest cost driving route, and an improved Dijkstra algorithm is employed to solve the model, where the improved Dijkstra algorithm inherits the original self-learning, self-organization, and self-adaptive characteristics. Furthermore, by converting the shortest route solution to the least cost route solution on the original basis, the algorithm is suitable for solving electric vehicle route planning considering time windows (EVRPTW) problems. Finally, simulation results show that the proposed algorithm can achieve an accurate minimum cost route.

To reduce the delay of task offloading in edge computing of the internet of vehicle and adapt the delay sensitivity and task repeatability of vehicle network, this paper presents a task offloading algorithm which utilizes the edge cache. When a task uploaded to the edge server and get corresponding results, Edge server evaluate factors including task total latency, size of result and popularity of the task to decide store the result in edge caching or not. If it is determined to be yes ,the following same task uploaded to the edge server will get the result from edge cache directly, reducing calculate delay of the task and operating cost of the entire system. The simulations show that this algorithm can reduce the latency and improve the availability of edge caching. In the ideal case. Compared with the original algorithm, the proposed algorithm can save 49% of the average latency and improve 31% availability of edge cache.