Design of solar greenhouse environmental monitoring and control on the basis of multinode data fusion

Abstract

Greenhouse environmental regulation can create an optimal environment for the growth of greenhouse crops and effectively improve their production conditions. This study aimed to develop an intelligent monitoring and control system for solar greenhouses on the basis of multisensor data fusion by integrating long range (LoRa) and WiFi communication technologies to increase the accuracy and reliability of environmental regulation. A median filtering algorithm and an adaptive weighted average data fusion algorithm were designed to improve the reliability of the data involved in the control system. A segmented control strategy was adopted to achieve automatic control of the solar greenhouse environment. Tests on data transmission and communication, analysis of the data fusion effect, and greenhouse temperature control tes ts based on the segmented control strategy were carried out for this system. The results showed that the success rate of data transmission of the system reached 99.8% and that the execution accuracy of the actuators was over 99%. Under the traditional single-node control strategy, the temperature was within the suitable range 41.96% of the time. Compared with the traditional single-node control strategy, the segmented control strategy based on data fusion maintained the temperature within the suitable range for 13.28% longer.