基于情景感知数据融合的农业物联网监测模型研究

Monitoring model of agricultural Internet of Things based on context aware data fusion

在传统农业逐步向智能农业发展的过程中,需要对农作物生长的各种环境数据进行监测。为此,设计一种能够监测农作物生长环境数据的系统。该系统采用无线传感器网络,基于ZigBee技术实现传感器节点间的数据传输。利用LEACH算法进行网络数据融合,提高无线传感器网络的存活时间。通过卡尔曼滤波完成节点间的数据融合,提升系统的数据采集精确度。试验结果表明,当网络传输300帧后,系统大部分节点仍然是存活的,与实际人工采集结果基本相同,温度误差小于0.2℃,二氧化碳浓度误差小于4 ppm,光照强度误差小于1 Lux。

In the process of developing traditional agriculture to intelligent agriculture,it is necessary to monitor various environmental data of crop growth.Therefore,a system for monitoring the growth environment data of crops is designed.The system uses wireless sensor network and realizes data transmission between sensor nodes based onZigBee technology.LEACH algorithm is used to integrate network data to improve the survival time of WSN.The data fusion between nodes is completed by Calman filtering,and the data acquisition accuracy of the system is improved.The test results show that most nodes of the system are still alive after 300 frames are transmitted over the network.The experimental results are basically the same as the actual manual acquisition results.The temperature error is less than 0.2℃,and the carbon dioxide concentration error less than 4 ppm as well as the light intensity error less than 1 Lux.