Artificial Intelligence and Internet of Things-Based Leak Detection Method for the Water Supply Network

Abstract

The good management and safe operation of the urban water supply network are of great significance to residents’ lives and industrial production. In view of the difficulties in supervision and leakage location of the urban water supply network, based on the technology of Internet of things and artificial intelligence algorithm, a leakage detection method of the urban water supply network is proposed. First of all, low-power, low-cost terminal detection equipment and gateway monitoring equipment are developed for remote data transmission through WiFi or cellular data networks. The data organization, storage, release and control are realized by using the data center software platform. Second, the leakage location model of the water supply network is established by using remote pressure monitoring data, and the accurate location of pipe network leakage is realized. Based on ALO and PSO optimization algorithms, the water supply network in an industrial area of a city in China is solved. Finally, the performance of the two optimization algorithms is compared and analyzed. The results show that the designed intelligent monitoring system of the water supply network can monitor the pipe network well. In addition, on the problem of leakage detection, the ALO algorithm is superior to the PSO algorithm in terms of optimization ability and search efficiency. The leakage monitoring method of water supply networks proposed in this study can provide a reference for the design and management of urban water supply networks.