Intelligent Agricultural Greenhouse Monitoring System Based on Cloud Computing

: In view of the increasing material needs of the people and the lack of resources, agricultural greenhouses can efficiently provide a variety of crop products to meet the needs of contemporary society. This research mainly discusses the research of intelligent agricultural greenhouse monitoring system based on cloud computing. This system adopts the B/S structure, combined with the multi-core technology of modern browsers, the universal browser can realize the various needs of customers for the system, which greatly saves the cost of the project. DTH11 temperature and humidity sensor detects data from the temperature and humidity sensor drive module, collects temperature and humidity data for it through the bus, and outputs the collected temperature and humidity data in parallel. The cloud platform database uses the lower computer temperature and humidity sensor module to automatically monitor the temperature and humidity dynamic values of the agricultural greenhouse, and display it on the 12864 LCD panel in the greenhouse in real time; the data information displayed on the data screen in the greenhouse is transmitted to the LABVIEW host computer display interface ; For the air and soil temperature and humidity in the greenhouse, the cloud platform database management program can record correspondingly according to the day; the management program can query the ambient temperature and humidity information according to the day or month; the management program can set the warning temperature and prompt the greenhouse in time differences in the external environment; the management program can generate reports, output the reports in accordance with the relevant requirements of greenhouse management, and print the temperature record curve and data. The error is analyzed based on the test results of the upper computer interface of the PC cloud platform. The difference between the tested soil temperature and the actual temperature is about 1 degree, and the error of the light intensity value is about 3%. This research provides a reliable solution for the artificial cultivation of crops with large environmental gaps.