The Data Fusion Technology Research Of City Sewage Monitoring System Based On WSN

Water pollution usually includes industrial water pollution and city life water pollution, it is very important to urban sewage and people’s life. Long time ago, urban sewage don’t need monitoring, sewage treatment is mainly composed of sewage collection system emissions nearby to the downstream water, and use the water purification function and the dilution effect for treatment. But as the numbers of population grow rapidly, along with the increase of the urban sewage water, which made a great influence to the downstream water. In this case, for preventing the urban sewage environment get worse, some measures must be taken to strengthen the urban sewage monitoring dynamics. The Micro Sensor technology and Wireless communication technology which based on micro electromechanical System (Micro Electromechanical System, MEMS) made the Wireless Sensor Network (Wireless Sensor Network, WSN) broad application prospect, and make it possible for WSN used in urban sewage monitoring. The basic function of Wireless sensor network is that, it can collect and transfer all kinds of information by a large numbers of sensor nodes in the monitoring area. How to reduce the amount of data transmission, and improve the transmission efficiency is one of the challenges wireless sensor network have to faced. Data fusion is one kind of technology aimed at reducing the network redundancy data, and the network data traffic, saving node energy, improving information collection for the purpose of accuracy, it is one of the important research subjects of wireless sensor network.The temperature parameter is an important decision variable in the Urban sewage monitoring, this paper based on the parameter estimation theory, put forward a kind of applied in urban sewage monitoring adaptive weighted fusion method. This method did not require monitoring data of the prior probability distribution, it is simple programming and small amount of calculation, which can effectively decrease the water inside temperature sensor measurement data error and improve the accuracy water temperature in the monitoring. As a result of the data fusion algorithm, the data transmission decreased, and the network energy consumption reduced, it can prolong the life of the network.