A Reliable Data-Driven Control Method for Planting Temperature in Smart Agricultural Systems

With the rapid development of intelligent computing technologies, the smart agricultural systems has gradually received more research attention. Precisely controlling planting conditions via intelligent means, it is expected to technically improve reliability of smart agricultural systems. For this purpose, this paper introduces the idea of big data fusion, and proposes a reliable data-driven control method for planting temperature in smart agricultural systems. Firstly, a variety of sensors are used to collect the values of environmental factors such as air temperature and light intensity during the experiment, and the “Digi” wireless communication technology is used to transmit the data. Then, the collected data is sent to the server through the 5G module, and the important data of the growth process is stored in the MySQL database. Taking the cultivation of yams as the investigation object, experiments on the real-world data are utilized to evaluate the proposal. And it is shown that the propose framework can work well to control temperature for yam planting from the perspective of data fusion.