Designing a particle swarm optimization model for efficient water management

This paper proposes a real-time monitoring system for pressurized water networks capable of detecting, localizing, and pinpointing leaks by utilizing particle swarm optimization (PSO) with sensors. The particle swarm optimization technique was used to find the minimal sensor placement for the identification of leaks in pipe networks. This technique was developed and integrated for accurate pipe leak detection in a wide variety of situations, leading to high efficiency. The system response was observed, and false alarms were noticed. About 4 false alarm frequencies were noticed for the water flow and no leakage mode, and 100% of the false alarms represented no flow and no leakage. In the case of water flow and leakage mode, a total of 5 false alarms were observed, of which 55% represent no flow and leakage and 45% represent no flow and no leakage. Meanwhile, the system false alarm was observed to reduce significantly when the system is pressurized for a long period of time. The PSO-based approach for leak detection in pipes minimizes false alarms, improves the accuracy and efficiency of leak detection, reduces energy waste, saves money, and helps prevent environmental damage.