Research on substation hazardous waste tracking and early warning based on big data

Min Cang; Yikang Huang; Shuang Wu; Xi Cheng; Dianmao Zhang

doi:10.1117/12.3038874

7 August 2024 Research on substation hazardous waste tracking and early warning based on big data

Min Cang, Yikang Huang, Shuang Wu, Xi Cheng, Dianmao Zhang

Proceedings Volume 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024); 132290Y (2024) https://doi.org/10.1117/12.3038874
Event: Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 2024, Nanchang, China

Abstract

Based on big data technology, this study designed and implemented a substation hazardous waste tracking and early warning system. Through detailed evaluation and comparative analysis of system performance, the results show that the system has excellent performance in data processing speed, early warning response time and prediction accuracy, which is better than the industry average. The experimental results show that the system has high efficiency and reliable operation characteristics, and has important application value in hazardous waste management. However, a number of issues were also identified during the experiment, including large-scale data processing performance and data quality challenges. Some suggestions for system optimization and improvement are put forward, including optimizing system architecture, improving data quality and improving early warning mechanism.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Min Cang, Yikang Huang, Shuang Wu, Xi Cheng, and Dianmao Zhang "Research on substation hazardous waste tracking and early warning based on big data", Proc. SPIE 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 132290Y (7 August 2024); https://doi.org/10.1117/12.3038874

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