Research on Greenhouse Intelligence Acquisition Technology Based on Wireless Data Transmission System in the Background of Big Data

In view of the current problems of insufficient capacity for agricultural facilities management and environmental monitoring, insufficient accumulation of relevant data for agricultural production, and low level of intellectualization of agricultural production, the greenhouse greenhouses were targeted for the application of the Internet of Things technology to design a real-time greenhouse temperature and humidity. Environmental information such as soil temperature and humidity, light, etc., and access to the Internet cloud control platform or mobile client through WIFI technology for data communication, real-time collection, display, storage and sharing of environmental data, and analysis of the collected data Judgment, automatic control of sprinkler motors and heating equipment intelligent greenhouse system. Experiments show that the system has the characteristics of simple installation, friendly interface, strong practicality, and easy extension. Android client and We-Chat public account realize the remote mobility management of the system. Good data interface helps big data collection and analysis, and can adapt to intelligence. Big data application needs in agriculture. Agricultural big data is a comprehensive application of big data technology, ideas and methods in the entire agricultural production and sales process. Its development has driven the development of agricultural informationization, and has continuously promoted the optimization of agricultural economy and the construction of smart agriculture. Although the importance of agricultural big data has gradually emerged, the research on agricultural big data still focuses on the analysis and processing of data. As the most important gathering link in the value mining of big agricultural data, it is still relatively weak. In recent years, the research on the collection of agricultural environmental information has developed rapidly. ZigBee networks and GPRS networks have been widely used, and most agricultural environmental monitoring systems are equipped with independent upper computers or mobile clients. Yu Pan and others proposed the ZigBee wireless sensor network combined with 3G network remote farm environment monitoring system. Zhao Wenbing and others proposed a long-range greenhouse monitoring system that combines ZigBee network, WIFI network and Android client. Han Liying also conducted this issue. The research has achieved certain results. Based on the rapid development of Internet technology, the increasing popularity of Internet of Things technology, and the growing maturity of cloud computing technology, the use of cost-effective single-chip microcomputers combined with environmental sensors to form an environmental monitoring module, real-time collection of environmental data for agricultural facilities; using WIFI technology to access the Internet cloud control platform Real-time collection and processing of data; real-time display of data through the mobile client, control of the implementation of the adjustment of environmental parameters, to form a closed-loop intelligent agricultural facilities system from information monitoring to information display and action control. In the management system of greenhouses, the temperature, humidity, carbon dioxide content, light intensity, and soil conditions inside the greenhouse must be mastered in real time, which can effectively ensure the growth of the internal crops in a good environment. At present, more greenhouses use different equipment to ensure the growth of good crops. For example: ventilation systems, external shading, heaters, etc. However, these devices require manual real-time monitoring operations, and there are many inconveniences. At present, in order to provide a better growing environment for crops, the various parameters in the greenhouse are accurately controlled, and a smart greenhouse management and control system is gradually established to implement effective intelligent adjustment of various parameters for automated management.