Research And Realization On Wireless Sensor Networks Coverage Scheme For Fire Monitoring Of Cotton Warehouses

With the rapid development of country’s economy, the demand of railway transportation of dangerous goods is increasing. Dangerous goods, which generally have the characteristics of inflammable, explosive or volatile, are prone to accidents, so the security of dangerous goods storage has been paid more and more attention. Generally, there is no network in the warehouses owing to the harsh conditions. And the scale of monitoring is not only large but also dynamic changing with the goods in or out. So it is difficult to insure the safety monitoring of dangerous goods warehouses stability and efficiently. Wireless Sensor Networks with high adaptability to harsh environment, the deployment flexibility and the advantages of no external power and network required has great application value to insure the safety of railway dangerous goods storage.The coverage problem is one of the key problems of Wireless Sensor Networks. Reasonable coverage strategies help to save the economic cost and reduce energy consumption, and it’s of significance for the system to keep work effectively. Taking the cotton warehouses fire monitoring systems as an example, this paper proposes and realizes the nodes deployment scheme and working nodes selection strategy that solve the coverage problems of Wireless Sensor Networks under the application background and enhance the effectiveness and accuracy of monitoring systems.Nodes deployment scheme is proposed and realized in the paper. Based on the coverage model of sensor nodes, the formulas of nodes number required for three regular polygon deployment schemes are derived and analyzed in detail. Meanwhile, optimal deployment scheme and its node coordinates calculation method are determined. The experimental results show that the nodes deployment scheme provides a complete solution and accurate nodes deployment coordinates. It contributes to reduce redundant coverage and avoid the coverage holes. Besides, it prepares important data for the working nodes selection strategy.Working nodes selection strategy is the focus of research and realized in the paper. Aiming at coverage problem of the dynamic target points and considering the network energy consumption, the Optimized Artificial Fish Swarm Algorithm, which can eliminate the adverse factors and has adaptive visual, is proposed and it has the ability of selecting working nodes more reasonable. The experimental results show that the working nodes set obtained through the Optimized Artificial Fish Swarm Algorithm can guarantee the coverage, reduce number of working sensors and ensure energy balance. Compared with Artificial Fish Swarm Algorithm, the Optimized Artificial Fish Swarm Algorithm, which has the higher iterative efficiency and better global search capability, can use fewer nodes to cover the target points, makes the energy consumption reduced by22.35%and prolongs the network lifetime efficiently.