Research And Implementation Of Intelligent Greenhouse System Based On WSN

With the rapid advancement of agricultural modernization in China,smart greenhouses based on wireless sensor networks have been rapidly promoted as an important technical means of agricultural modernization.The main function of the WSN intelligent greenhouse system is to monitor and collect the environmental factors in the greenhouse and adjust the environment in the greenhouse through the feedback control system to make the crops in the greenhouse have the best growing environment,thereby promoting the yield of crops and improving the quality of agricultural products.At present,most WSN smart greenhouse systems mainly use WiFi,Zigbee,Bluetooth,3~5G and other technologies to achieve data and command transmission.However,the smart greenhouse has the following characteristics:(1)in the wild,power supply is a problem;(2)The dense crops in the greenhouse will seriously affect the radio communication;(3)There is no carrier base station.Therefore,using WiFi or 3~5G technology to build a smart greenhouse system is not feasible in the mountains,and Zigbee and Bluetooth technology are seriously interfered by obstacles.In a complex greenhouse,the transmission distance is limited and the link quality is not high,which will be serious.Affect the transmission of data.Based on the above analysis,this paper adopts an emerging narrow-band wide-area Internet of Things technology,LoRa.The wireless sensor network is generally powered by a battery,has a strong penetration capability,and has a transmission distance of up to 15 km,and is compatible with traditional WiFi and Zigbee.Bluetooth,3~5G technology has lower energy consumption,and one battery can last for several years.The use of LoRa technology to build a smart greenhouse information transmission network can solve the problems of field power supply,no base station,obstacles and other obstacles,so it has high reliability and feasibility.In order to optimize the living conditions of crops in greenhouses,an expert knowledge base based on deep learning method(DNN)was studied.The environmental factors collected by LoRa sensor network were input into DNN model for training and prediction,which can be based on current environment.Information output scientific and reasonable control decision-making instructions.Then the instruction is sent to the feedback control system,which includes fluorescent lamps,sun visors,new fans and drip irrigation,which timely adjusts the environmental information in the greenhouse according to the decision-making instructions,so that theenvironment in the greenhouse reaches the best living conditions of the crops.Finally,a visualization system based on Kriging interpolation method is studied.The distribution of environmental factors is displayed in the system by using the depth of color.The test and experimental results show that Intelligent Greenhouse System Based on WSN can effectively collect the environmental information in the greenhouse,has a low packet loss rate,and can make scientific decisions in intelligent decision-making and feedback control.Effectively adjust the greenhouse environment,and finally the system can visually display the distribution of environmental factors in the greenhouse.