Research And Application Of Wireless Sensor Networks In Forest Environment

The application of wireless sensor networks(WSN)technology promotes the modernization of forestry.WSN application technology in forest area is an important research topic of forestry sustainable development in China,and it is also a research hotspot of forestry ecological monitoring at present.For the application of forest wireless sensor network,the problem of limited energy supply and low delay data transmission in forest environment should be solved first.Because of the large area and uneven density of trees,the dynamic change of forest height,and the easy blocking of signals,it is easy to cause the difficulties of fast node energy depletion,short network life cycle and large data transmission delay in the forest environment.Secondly,the application of wireless sensor network usually takes the maximum data collection as the core,but the contradiction between the high data collection rate and the limited energy supply is inevitable.Therefore,it is necessary to build the maximum data collection rate model with the limited energy supply as the constraint to ensure the optimal collection condition of wireless sensor network.Starting from the application of wireless sensor network technology in forest environment,this paper studies the application of wireless sensor network in forest based on the analysis of energy self-collection and permanent function of sensor nodes,transmission and routing strategy of sensor nodes,data collection,fusion and fuzzy reasoning decision-making process of fire risk early warning,so as to provide overall solution to the problem of the forest fire early warning based on Rechargeable Wireless Sensor Network.The main research contents are as follows:(1)The dynamic energy supply in the rechargeable wireless sensor network is analyzed,and the transmission control protocol based on energy is proposed,which effectively improves the data transmission efficiency.In the rechargeable wireless sensor network,the average delay time of network E2E(end-to-end)is calculated according to the number of nodes on the data transmission link.If the network delay is far greater than the average delay time in the process of data transmission,it shows that there is still a lot of space to reduce the network delay,so the transmission control model can be used to reduce the data transmission delay.Considering the limitation and time-varying of energy acquisition,the working time of nodes is divided into multiple time slices and shared with neighbor nodes.Using the work schedule mechanism reduces the energy consumption of nodes for neighbor discovery and improves the transmission efficiency.(2)Analyze the average delay time,and propose a transmission control model to realize the timely transmission of data.The energy transmission control model fully considers the time-varying and uncertainty of node energy acquisition.When the node energy changes,especially when the energy acquisition is high,in order to improve the energy utilization rate of the node,the node can adjust the transmission distance at any time according to its own energy change,without changing the number of working time slices in the work schedule,so as to ensure the stability of the work schedule.This model is mainly used to control the transmission radius of nodes to reduce the delay.Nodes skip the nearest neighbor nodes and transfer the single hop distance to nodes to directly transmit nodes in the multi-hop range.(3)Analyze the situation of network data collection,put forward a design model with the maximum data collection rate of network nodes as the optimal goal,and realize the maximum data collection.According to the energy conversion rate and data flow conservation principle of sensor network nodes,a linear programming model with the maximum data acquisition rate as the optimal goal is established.This model can maximize the data collection rate of all source nodes in the network.For each node,if the data loss and energy loss are not considered,the data sent by the node is equal to the sum of the data received by the node and the data collected by the node,and the energy consumed by the node will not be greater than the energy obtained by the node.Based on this,the maximum data collection rate model of the network is established.(4)This paper analyzes the characteristics of heterogeneous network data,and proposes a fusion strategy of forest environment factors from spatial and temporal attributes to reduce data redundancy and bandwidth consumption.On the basis of research content(3),add data fusion algorithm,propose the optimal goal linear programming model based on data fusion algorithm,use optimization technology to solve the upper limit of data acquisition rate of network nodes,and establish the low delay transmission and high-speed data acquisition communication link with data fusion.(5)Aiming at the low delay transmission of data and the maximum collection rate of node data,a forest fire risk early warning system based on fuzzy inference strategy is proposed to timely warn forest fire risk index.According to the characteristics of the studied area,a large number of wireless sensor nodes are deployed in the area with high forest fire incidence to monitor the forest environment and meteorological conditions in real time.At the same time,the influence of the flow of people in the monitoring area on the forest fire,the time factor and the historical fire situation are also considered in the system,and the causes of the forest fire are analyzed more comprehensively.The proposed early warning system will automatically and flexibly carry out weighted fuzzy reasoning,which has larger scale flexibility.The overall research goal of this paper is to focus on the forest environment,realize the forest fire early warning problem of low delay and high acquisition rate performance of Rechargeable Wireless Sensor Network,focus on solving the forest environment factors,node energy self-collection and energy consumption management,achieve the purpose of "permanent deployment",and put forward the forest potential based on fuzzy reasoning by considering the key monitoring area and network deployment strategy.The research of fire riskidentification technology provides the necessary technical support for the forest fire early warning of wireless sensor network.