The Data Fusion Algorithm Based On WSN Face To Sewage Monitoring System

Water is the source of life. It not only constitutes an important part in the body’s tissues but also is the essential energy to the existence of human beings. Whether the quality of water is good or not has a direct influence on the human’s normal life. With the continuous development of modern science and technology, industry and economy, more and more pollution affects the quality of water. Real-time control of water quality can help people to the utmost reduce the water pollution harm to people’s bodies and their daily life so as to guarantee people’s normal life.This research is part of the project of Shaanxi science and technology development, which focuses on the monitoring of Wei river and four drain outlets in Xi’an city. In view of the problems such as the complicated steps in previous monitoring system, low degree of automation, untimely collection of water quality parameter, low precision and easy damage to the ecological environment of water, also high cost investment, we put forward a new type of urban sewage monitoring system based on wireless sensor network (WSN), and conduct the research of data fusion algorithm so as to prolong the working life of the network.According to the actual characteristics of outlets of Xi’an city, we make the implementation plan for urban sewage monitoring system. Depending on measurement parameters of water quality and the condition of the Wei river pollution, we choose temperature, dissolved oxygen (DO), turbidity and power of hydrogen (PH) and the ammonia nitrogen (NH3N) as the measured parameters of the urban sewage monitoring system. And meanwhile the data transmitted by the system is processed as well. Routing layers by cluster member nodes joined the average filtering algorithm and to set the parameters corresponding confidence interval, of sensor collected original data to deal with the redundant; Cluster heads in using the adaptive weighted data fusion algorithm to realize the comprehensive processing of similar sensor data transmission; Base station in classifying water environment by using BP artificial neural network, determine the water quality pollution.Finally, various levels of data fusion algorithm is verified by simulation with the help of NS2 and MATLAB software and the results showed that the data fusion algorithm based on the premise of meeting the demand of system data can reduce energy consumption, improve the channel utilization, and effectively prolong the life of the water monitoring system.