| As a basic agricultural facility,agricultural greenhouses play an important role in increasing crop yield、improving production management efficiency and enhancing crop quality.With the development of science and technology,it is essential to be able to monitor the growth environment of crops in real time and respond accordingly to enhance the productivity of agricultural planting.The traditional monitoring methods often have the problems of low detection accuracy and waste of resources.This thesis uses the characteristics and advantages of wireless sensor networks(WSN)to design and implement an agricultural greenhouse environment monitoring system based on WSN,which can collect the information of crop growth environment in the greenhouse in real time,find the abnormal environment in the greenhouse in time and respond to it.The system can reduce the losses caused by the delay of information misinformation and ensure the safety of agricultural production.The main research contents of this thesis are as follows:Firstly,this thesis elaborates the important significance of WSN technology in the modern agricultural greenhouse environment monitoring system,briefly introduces system structure of WSN and the technical characteristics.It also focuses on the definition、classification、causes of abnormal data,as well as the characteristics of abnormal data detection algorithm in WSN.Secondly,aiming at the problems of high false positive rate and high communication overhead of abnormal data detection in wireless sensor networks,this thesis proposes an anomaly detection algorithm based on sliding windows and confidence.The algorithm uses environmental interference factor to quantify the uncertainty in the monitoring environment,and establishes abnormal data interference interval to identify abnormal data in the sliding window.The algorithm proposes a calculation method of data anomaly degree to predict the source of anomaly;Then,it introduces multi-communication radius to divide the optimal neighborhood and uses the relative entropy to calculate the node information confidence;According to the information confidence of nodes,the origin of the anomaly is identified cooperatively.The algorithm proposes in this thesis takes into account the uncertainty impact of the environmental factors in the monitoring area on the determination of the detection results.It can ensure high detection accuracy while controlling the false positive rate at a low level,and the algorithm has good fault tolerance performance.Finally,the abnormal data detection algorithm proposed in this thesis is applied to the agricultural greenhouse environment monitoring system.According to the application requirements of the system,the agricultural greenhouse environmental monitoring system based on WSN is divided into two parts: upper computer and lower computer.The upper computer client system uses B/S architecture,IDEA as the development tool,and Java language to complete the development;The lower computer terminal node uses CC2530 chip to carry various sensors to realize the collection of air temperature and humidity,light intensity,carbon dioxide concentration in the shed and the detection of abnormal data.The test shows that the system is stable and efficient,and can meet the actual needs of modern agricultural greenhouse environmental monitoring. |
