The Application Of Wireless Sensor Network In A Remote Environment Monitoring

With the accelerated process of industrialization, heavy metal pollution occurrences frequently, Zijin Mining, Cu pollution and a series of incidents rocked the whole country, which seriously harm to people's living environment and physical health, heavy metal pollution is urgent. Currently the most effective measure is to detect the presence of heavy metals, however, because of a vast, complex terrain, to the monitoring of heavy metal pollution has caused big problem. In this paper, put forwards the type and concentration of heavy metals in construction of wireless sensor network systems monitor the environment, and provide the reference information for the adoption of the program timely.This article first does the analysis for present heavy metal pollution in China, and the advantages of the wireless sensor network applications in environmental monitoring, then put forwards the wireless sensor network system architecture and design structure of wireless sensor nodes on the basis of wireless sensor network research status, structure, characteristics, design principles, key technologies, that is the system used in all FFD nodes, but some of FFD node implement RFD function, which can enter the sleep mode to reduce energy consumption. Also briefly introduced the working principle of bio-sensor group information collection node developed with Chinese Academy of Sciences Environmental Ecology Center together, and related information of JN5148 information processing module from Jennic company.Secondly, the system selected the ZigBee technology, adopted ZigBee mesh topology and AODVjr routing algorithm according to the system's communications'needs, and for the comparative analysis of existing wireless communication technology. In the layout of system network mesh topology, give full consideration the energy consumption, proposed to increase the FFD nodes'density near with the base station and adopt the RFD nodes at the edge of the network. Meanwhile, proposed the improvements on the original AODVjr algorithm; FFD packets forwarded to the purpose of child nodes must be a child of their own according to energy level redirect packet; design RFD refused to receive the transfer of non-parent packet and add two agreements at the same time, full use of node energy, balance the network load through conditional switching. Experimental results show that the energy saving methods and routing algorithm of the system, energy-saving effect is obvious, improve the network use efficiency.The study found that can improve the intelligence of wireless sensor networks during monitoring heavy metal pollution through handling collected data come from the biosensor, that is to say, can directly predict the type and density of heavy metals, also proposed to deal with data by artificial neural networks through the research in the feature of biosensor collected data and relative knowledge of heavy metals. In view of insufficient data from the experiment at present, the article proposed the mathematical formula simulated fluorescence of certain concentration's biosensor, simulates fluorescence data of each biosensor successfully by choosing three representative heavy metals elements. Then the article put forwards that the artificial neural networks apply to data processing of biosensor from reverse modeling ideas, separately use the probabilistic neural network for classification of metal and corresponding BP neural network to the forecast of heavy metal density, the efficiency is good in heavy metal classification and concentration forecast shown from the experimental results.This article applied wireless sensor network technology to the field of environmental monitoring of heavy metals successfully, proposed the good solution to solve the heavy metal detection and hard monitoring in the system architecture, design philosophy, node design, network topology arrangement, the routing algorithm improvement, and acquisition data processing and other work, promoted the general promotion of wireless sensor networks in our country.