Intelligent Water Pollution Source Identification and Localization in Wireless Sensor Networks

Emergency management of pollution accidents in surface water is an important issue in environmental protection. Identification and localization of the water pollution source is crucial for quick treatment and disposal, which can reduce harmful influences. Aiming at multi-sensor water quality data fusion and energy-aware pollution source searching, an intelligent water pollution source identification and localization method is studied based on wireless sensor networks (WSNs). In the designed WSNs for water quality monitoring, multiple sensors are embedded in two types of sensor nodes, unmanned ships and micro stations, which are deployed on water and shore respectively. One algorithm utilizing radial basis function network (RBFN) and entropy is proposed for pollution factor identification among total organic carbon (TOC), nitrate nitrogen, turbidity, dissolved oxygen (DO), conductivity, potential of hydrogen (pH), etc., and another algorithm utilizing improved particle swarm optimization (PSO) is proposed for pollution source localization in the risk areas. The results of simulations and experiments show that the water pollution source is identified and localized efficiently with the proposed method and the energy consumption is reduced during searching.