Design and implementation of mobile greenhouse environmental monitoring system based on UWB and Internet of Things

To grasp timely and conveniently environmental information such as temperature and humidity in the greenhouse, a mobile greenhouse environment monitoring system was designed, which realized the mobile monitoring of greenhouse environmental parameters. According to the improved double-side-two-way-ranging algorithm, the distance between each base station and the tag was calculated. The NLOS error was judged by the normalized residual distribution of distance, and the improved incremental Kalman filter algorithm was used to eliminate the NLOS error, and the Chan algorithm was used to calculate the accurate tag position. The mobile greenhouse environment monitoring system was composed of a remote monitoring platform, mobile workstation, and UWB positioning module. The remote monitoring platform was responsible for displaying the location information of the mobile workstation in real-time, controlling the movement of the mobile workstation remotely, displaying and storing the environmental information uploaded by the environmental information monitoring module. Mobile workstation mainly included mobile chassis, drive module, control module, environmental information measurement module, UWB positioning label, and communication module. As the specific executor of the command, the mobile workstation was responsible for receiving and executing the mobile command issued by the monitoring platform, collecting and sending the measured temperature and humidity and other environmental parameters to the monitoring platform in real-time. The remote monitoring platform and the mobile workstation communicate timely through the wireless network. The UWB positioning module included a positioning tag, positioning base station, and a computing unit. The positioning tag was installed on the mobile workstation to mark the position of the mobile workstation in the greenhouse. The positioning base station was responsible for calculating the distance between each base station and the tag and sending it to the computing unit by serial communication. The computing unit calculated the position of the tag in the greenhouse and displays it. The software of the environmental monitoring system consisted of a position information interaction layer, environment information monitoring layer, and motion control layer. The position information interaction layer was a real-time positioning program based on windows, which displayed the position of a mobile workstation in the greenhouse. The environmental information monitoring layer was an Android-based program to collect and display environmental information measured by sensors, drawing the hourly temperature and humidity change curve. The motion control layer was an Android-based remote control program, which sent motion instructions to the mobile workstation through the remote communication protocol to control the stable and safe movement of the mobile workstation in the greenhouse. The remote control and positioning accuracy-test showed that the maximum lateral deviation of the system static positioning was 7.92 cm, the maximum longitudinal deviation was 7.98 cm, and the average value of both horizontal and longitudinal deviation was less than 5 cm. When the mobile workstation was running at a speed of 0.4 m/s, the maximum lateral deviation of dynamic positioning was 8.7 cm and the average lateral deviation was 4.7 cm. Through the stability test of environmental information collection, the average data loss rate of the collected greenhouse environmental parameters uploaded to the remote monitoring platform was 2.78%, the environmental information collection was stable. The relative errors of temperature, humidity, light intensity and carbon dioxide concentration were less than 0.63%, 0.34%, 0.70%, and 0.67%, respectively, the environmental monitoring accuracy was high. The system adopted modular hardware structure design and layered software structure design, taking into account the requirements of the system for data through flux and response speed. Combined with the remote monitoring platform, it realized remote control, precise positioning, and remote real-time monitoring of the greenhouse environment. The system could have certain reference significance for the development of remote environmental monitoring technology and greenhouse precise positioning technology. © 2020, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.