基于物联网的农业环境数据收集系统设计

Design of Agricultural Environment Data Collection System Based on the Internet of Things

设计了基于物联网的农业环境数据收集系统,该系统使用支持向量机回归(SVMR)算法来处理原始数据,并预测日常空气温度、相对空气湿度和风速值,以帮助预测有害病菌在农田的传播。结果表明:预测的平均空气温度值和实际测量值平均绝对误差为1℃;预测的平均相对空气湿度值和实际测量值平均绝对误差为5%;预测的平均风速值和实际测量值平均绝对误差为1 km/h。该系统通过物联网访问环境数据,有助于田间作物管理人员更好地管理和预防病菌蔓延。

An agricultural environment data collection system based on the Internet of things is designed. The system uses support vector machine regression （SVMR） algorithm to process the raw data, the predict daily air temperature, relative humidity and wind speed value, in order to help predict the spread of harmful bacteria in farmland. The experimental results show that the mean absolute error of predicted average air temperature and the actual measured values is 1 ℃. For the average relative air humidity, the mean absolute error of predict values and the actual measured values is 5%. The mean absolute error of predict the average wind speed value and the actual measured values is 1 km/h. The system data are accessed through the Internet of things environment. Eventually, the system will contribute to the field crop management staff to better manage and prevent the spread of germs.