LI Xu, LIN Feng, ZENG Jie, LI Hongyuan, LI Xiaoyu. RESEARCH AND PRACTICE ON DIGITAL CONTROL OF URBAN DRAINAGE SYSTEM UNDER WATER ENVIRONMENT OPTIMIZATION[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(11): 134-140. doi: 10.13205/j.hjgc.202311021
Citation:
LI Xu, LIN Feng, ZENG Jie, LI Hongyuan, LI Xiaoyu. RESEARCH AND PRACTICE ON DIGITAL CONTROL OF URBAN DRAINAGE SYSTEM UNDER WATER ENVIRONMENT OPTIMIZATION[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(11): 134-140. doi: 10.13205/j.hjgc.202311021
LI Xu, LIN Feng, ZENG Jie, LI Hongyuan, LI Xiaoyu. RESEARCH AND PRACTICE ON DIGITAL CONTROL OF URBAN DRAINAGE SYSTEM UNDER WATER ENVIRONMENT OPTIMIZATION[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(11): 134-140. doi: 10.13205/j.hjgc.202311021
Citation:
LI Xu, LIN Feng, ZENG Jie, LI Hongyuan, LI Xiaoyu. RESEARCH AND PRACTICE ON DIGITAL CONTROL OF URBAN DRAINAGE SYSTEM UNDER WATER ENVIRONMENT OPTIMIZATION[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(11): 134-140. doi: 10.13205/j.hjgc.202311021
Drainage and water environment digitization is a crucial tool for achieving the quality and efficiency of drainage systems and enhancing water environments. Take the S River Bay watershed in a southern city as the case, we analyzed the key factors that trigger the sewage overflow pollution. We proposed a framework for the digital management of drainage-water environments and developed a digital solution concept encompassing basin-wide online monitoring, chain-wide closed-loop control, scene-wide intelligent analysis, joint dispatching of all elements, and system-wide supervision. Leveraging an informatization platform combined with spatial big data, Internet of Things (IoT), machine learning, and other emerging technologies, this research focused on addressing drainage issues remediation, intelligent identification of abnormal liquid level events, long-term diagnosis and treatment of small watersheds, joint scheduling of sewage operations, and "one network unified management" digital application scenarios for water environments. The results are promising and expected to provide valuable insights for the similar areas.
Zhiying X, TING Y, LARI N M.Method of cumulative anomaly identification for security database based on discrete Markov chain[J].Security and Communication Networks, 2022.