水稻物联网监测系统研究

With the development of Internet of Things technology, the traditional agricultural production relying on human experience has been gradually transformed into precision agriculture. In this paper, a paddy Internet of things monitoring system with strong expansibility and good performance is constructed, which mainly includes three parts: embedded device end, server and evaluation method. In this paper, an improved XGBoost algorithm for farmland environment is proposed, which is used to establish an assessment model of paddy field growth environment and to evaluate the current growth state with sensor data. According to the data type of farmland sensor, a protoBuf protocol which is easy to extend is designed to improve the data transmission efficiency. In addition, this paper decouples the system server through Kafka message middleware, which reduces the dependence among the modules of the system and makes it easy to maintain and expand. Finally, the large data generated by farmland is applied to guide agricultural production and promote the construction of modern agriculture.