Micro-station For Environmental Monitoring Based On Internet Of Things And Edge Computing

At the moment,the problems of environment caused by the rapid development of economic are becoming more and more serious.Effective monitoring of pollution is the first prerequisite for environmental protection.China is in the critical period of changing from traditional manual sampling monitoring to automatic environmental monitoring system.With the continuous innovation of sensor,communication and embedded technology,the monitoring system also needs to be updated,which has great research significance.The research direction of this paper is to study the key technologies in the construction of environmental monitoring micro-station under this background.The main work of this paper is as follows:(1)The research background and significance of environmental monitoring micro-station and environmental monitoring system are expounded.The application status of IoT in the field of environmental monitoring at home and abroad is analyzed.Also,this paper discussed the key problems and common algorithms in data acquisition and processing of environmental monitoring micro-station system(2)Based on the current general architecture of the Internet of Things,this paper studied the model of the IoT suitable for environmental monitoring micro-stations,and further analyzed the key technologies in the IoT.At the same time,to lighten the computing burden of cloud platforms,this paper puts forward the application model of edge computing,and gave the edge computing architecture,which provides a reference for the further application and development of the IoT in the environment.(3)In order to solve the problem of node deployment in environmental monitoring,this paper proposed an optimized particle swarm optimization algorithm based on fuzzy perception and spatial weight(WFSPO).For the model itself,the spatial weight was introduced to describe the importance of the region,and the fuzzy perception model was established to describe the perceived performance of the nodes,and the weighted coverage was used as the evaluation function of the algorithm.The biggest feature of WFSPO algorithm is to fully tap the characteristics of particles in the model,and using gravity based on weight to optimize particle evolution equation,so that the algorithm has better optimization ability.Through a lot of simulations,this paper analysised algorithm parameter selection problem,and compared with the PSO、VF、EABC algorithm,WFSPO algorithm has faster iteration speed and higher target coverage,and it can save about 13%of nodes.(4)According to analyze the functional requirements of environmental monitoring,this paper designs a set of environmental monitoring micro-station based on IoT and edge computing architecture.In this paper,Hardware and software are designed for edge devices.For hardware,this paper adopted the multi-core design idea to separate data acquisition and processing,which gives the edge devices the ability of initial edge calculation.For software,the protocol of data exchange based on ProtocolBuffer,MQTT and TSL is adopted to realize lightweight,real-time and secure data transmission.At the same time,according to the edge computing model,the this paper designed PM2.5 data prediction service based on LSTM.After testing,the system has been initially built successfully,which can realize real-time collection,transmission and edge processing of environmental data,and maintain strong stability and real-time.At the end of the paper,the research work of the full text is summarized,and the next goal and research direction are discussed and prospected.