Research On Optimization Of Low-power Wireless Vehicle Detection Sensor Networks

Vehicle detection technology is an important part in intelligent transportation system. Using wireless sensor network gather and transfer vehicle information has significant advantages compared with traditional methods, and has an extremely prospect in intelligent transportation field. Energy limit of Wireless vehicle detection sensor network is an important factor which restricted its development. Therefore, the research on how to optimization design the wireless vehicle detection sensor network to reduce the energy consumption has important practical significance.The thesis firstly analyzed the structure of wireless vehicle detection sensor network in detail. The Layout method of wireless network sensors and information collection method are analyzed. Based on the energy consumption of different module, it analyzed the energy transmission model of wireless sensor networks. An algorithm of wireless vehicle detection sensor network node layout is presented, On this basis, design of a wireless vehicle detection sensor network relay node layout program, the algorithm based on the collection node relative position in the network to relay node layout, can effectively avoid the long-distance data transmission, to reduce network energy consumes purposes; proposed for vehicle detection sensor networks, distributed lossless compression algorithm, the algorithm combined with wireless sensor networks, vehicle detection feature, by analyzing the internal relationship between frames, using relative code to remove the redundancy, compression rate of more than 40%. The thesis developed a wireless vehicle detection sensor network monitor platform based on C/S mode, the platform realized real-time data acquisition, remot users monitoring, analyzing and processing of the sensor node data. Users'requirement of the wireless vehicle detection sensor network had fulfilled.In order to validate the node optimization algorithm and the data compression algorithm, the thesis used this platform to carry out data collection at Beijing Jiaotong University, and simulated the data. The results show that the energy consumption of wireless sensor network can be effectively reduced after using the node optimization algorithm and the data compression algorithm, achieved the anticipative goal.