Liu Congning

Research in Automobile Exhaust Gas of Sulfur Dioxide and Nitrogen Dioxide Monitoring WSN and Optimization Coverage Algorithm

For help solving the air pollution problem caused by the mass increasing of Sulfur Dioxide And Nitrogen Dioxide automobile exhaust gas, we have designed a Zigbee wireless monitoring network to monitor the Sulfur Dioxide And Nitrogen Dioxide in automobile exhaust gas, and build this monitoring system in hardware and software. Also, we use a Artificial Fish Swarm Algorithm to optimize the network covering area. According to a simulation result, the network coverage could be increased to more than 95%, and it makes the network nodes more efficient, reduced the redundancy nodes, lower the system energy consumption, to meet the design qualification.

Data Mining Research in Early Warning Model of Chlorine Gas Monitoring Wireless Sensor Network

Massive historical data are stored in chlorine gas monitoring network. So that prediction algorithm of data mining is used to dig historical data not only can make the redundant data reused, but also can forecast the network trend and improve the network early warning model. The chlorine gas monitoring wireless sensor network based on ZigBee was designed in this paper. Then Fletcher-Reeves algorithm was added to dig historical data in the network, forecast the network trend and improve the early warning model. The predicted concentration of chlorine data were trained by data mining model. The maximum relative error between predicted concentration and measured concentration was 11.08%, and the maximum average error was 7.36%. And it can satisfy actual requirements.