KEYWORDS: Bridges, Data modeling, Structural health monitoring, Sensors, Clouds, Acoustic emission, Data processing, Safety, Computing systems, Data storage
With the continuous development of social economy and the continuous increase of transportation, bridges play an increasingly important role in transportation. Bridges are the basis of accelerating urbanization, and also the key to ensure safe and smooth transportation. With the increase of traffic load, the safety problems of bridge structures also appear. Due to the limitation of construction level, the understanding of structural complexity and the influence of external unpredictable environmental factors, people can not effectively understand the damage of the bridge structure and accurately evaluate the operation and maintenance of the bridge, resulting in a series of traffic accidents. In view of the above problems, this paper carried out the research of bridge health monitoring system based on "cloud edge". It takes acoustic emission (AE), capacitance, impedance, optical sensor, etc. as the basic sensing unit, and combines edge based big data processing with edge computing model as the core and centralized big data processing with cloud computing model as the center. A bridge health monitoring platform based on the cloud-edge-end architecture is designed, which can effectively process data in real time and realize cloud backup, so as to achieve real-time assessment and diagnosis of bridge operation safety without interrupting bridge traffic functions.
With the rapid development of the economy and the continuous improvement of people's living standards, the production of daily waste has increased sharply. In order to effectively realize waste reduction and resource recycling, garbage classification has been widely promoted. However, despite various publicity efforts, there are still problems with unclear, ambiguous, and incorrect garbage classification among residents. To address these issues, an intelligent garbage classification system based on vision and speech recognition technology has been designed. The system includes an intelligent management terminal at each park's garbage collection point, which collects voice and image information for processing and analysis on a central server. The terminal is equipped with the ability to control the opening and closing of the intelligent garbage can lid and monitor the status of the garbage collection points. Furthermore, a supporting mobile application is available, enabling users to learn about garbage classification knowledge online and to carry out proper garbage classification. The implementation of this intelligent system solves the problem of garbage classification, which improves the efficiency of garbage treatment and provides significant practical and social value.
KEYWORDS: Engineering education, Process engineering, Systems engineering, System integration, Statistical analysis, Software engineering, Quality systems
Engineering education accreditation is an important way for colleges and universities to promote the reform of engineering education and the construction of "New Engineering and Technical Disciplines". There are many problems in the process of promoting engineering accreditation, such as the fragmentation of teaching data, the complexity of process management, the heavy calculation workload and human handling errors of achievement evaluation. In order to solve these problems, an accreditation management system of engineering education is designed and developed based on B / S architecture. The system supports manual input and batch import of graduation requirement index points, index points support matrix, course objectives, assessment methods, course scores and other information. The system can automatically calculate and generate achievement evaluation reports. The system also supports comparison and analysis of evaluation data of different grades. The results show that the system can save a lot of manual work and effectively improve the efficiency of the accreditation process.
With the continuous development of cloud computing technology, the application of cloud computing technology in all walks of life has become a trend. Combined with the current situation of university computer laboratory construction, this paper introduces the application scheme of cloud computing technology in computer laboratory construction and management from the perspective of cloud computing, virtualization and other technologies. Compared with the traditional laboratory construction scheme, the laboratory system based on cloud computing can effectively reduce the laboratory construction and management cost, improve the management efficiency and resource utilization, and achieve the sharing of experimental resources. Students can experiment on demand anytime and anywhere.
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