Design and Implementation of an Intelligent Environmental-Control System: Perception, Network, and Application with Fused Data Collected from Multiple Sensors in a Greenhouse at Jiangsu, China

Big-data (BD) can contribute to the perceptive layer in the Internet of Things (IoT). BD for environmental factors at the tiny scale has to be obtained by simultaneously monitoring and fusing data collected from multiple sensors. In this study, we designed an intelligent environmental-monitor-control system for the precise culture of grape ( Vitis vinifera “Wink†) in greenhouse IoT. Sensors were equipped to obtain multiple types of data, which were then fused at the gateway and stored, analyzed, and modified in the background. Environmental factors included air temperature, air humidity, illumination, soil moisture, and CO 2 concentration. Also, videos and images were recorded during the grape growth. The whole system was identified on an online platform with a static IP and a domain name. The fore- and backgrounds were communicated to each other by a real-time connection, and a database was activated whilst the website was open at the foreground. Results indicated that fused data can be successfully stored, transmitted, and treated for dotted graph creation and background management on a self-built online platform. Our study illustrated the availability of data fusion for BD and supplied a feasible instance for the implementation of this technique in IoT for the greenhouse environment.