Research Of Several Key Techniques For Building Diaster Rescuing System Based On Sensor Network

With the development of our society and economy, the quantity of huge buildings, with more complex structure, is increasing rapidly. This brings a stricter requirement for the rescuing system in sudden disasters such as fire and blaster. Owning many advantages such as independence on infrastructure, distributed database and high reliability, wireless sensor network(WSN) can provide a different new ways for huge building disaster rescuing system. Based on traditional fire-alarm system with field bus, this paper introduces wireless sensor network into huge building field to build up a stronger and more efficient rescuing system with accurate localization ability, fast information transmission and longer lifetime. In this paper, the exploration and research of theory and application are focused on several key techniques.Firstly, the traditional fire-alarm system based on field bus is developed for large buildings. Based on advanced microcontroller, a solution with multiple protocols combination and modular design is proposed and implemented. This brings the system good scalability to adapt different requirement. At the same time, a portable information terminal for disaster rescuing is developed. It can acquire real-time information from the rescuing network and implement an efficient interaction with multimedia message between the rescuing personel and control center. Thus, the rescuing personel is able to build a fluent communication with their commander. This is helpful to improve the rescuing efficiency.Secondly, this paper surveys on the methods for fire point localization and multi-target localization with wireless sensor network. Based on the Gaussian space multi-peek fire model, the multi-source localization algorithm is improved to generate a new EM-MR method. Then, Tabu search algorithm is used for parameters estimation and acquires excellent result. The proposed method has improved accuracy of the localization effectively and decreased the computational complexity. A model for acoustic source localization is also built up. Improved MR method and Tabu algorithms are applied into multiple acoustic sources localization and reveal good performance. Simulation result verified the effectiveness of the proposed algorithms.Thirdly, the determistic deployment of wireless sensor network in building space is researched in areas with obstacles. Sensor’s detection models and coverage quality are set up. Based on the probabilistic detection model with false alarm rate, this paper proposes a new deployment method. Watershed algorithm is employed to choose the deploying sub-area. Then Delaunay Triangulation is used to generate the candidate positions for new nodes. With the evaluation mechanism, the placement of WSN nodes is realized orderly and efficiently. Contrast with different methods such as random deployment, MAX_MIN_COV and MAX_AVG_COV, the proposed method attains higher detection probability and better coverage uniformity.Due to the strict requirement of fast and accurate information transmission during building disasters, this paper adapts a data fusion tree in cluster. Furthermore, we creates a fusion tree with the smallest transmitting nodes and the shortest path based on the apex coverage technology. Then, the nodes’fusion time is assigned according to the tree structure to decrease the transmission delay and conflicts. With the Graph Theory and clustering technology, a distributed heterogeneous data fusion C-means algorithm is proposed based on clustering protocol and apex coverage for data in clusters. Simulation experiment is implemented and verifies the algorithm’s effectiveness.Finally, a new wireless sensor network node based on Zigbee is designed because current available nodes always show technical secret-keeping and can not be used for routing protocol and specific signal detection. On analysis of the Zigbee protocol struction and the features of different layers, a micro-controller and a Zigbee chip is used to form the node’s hardware. TinyOS from Micaz platform is ported into the new node and works for the modular function. An application for star-network of multiple WSN nodes is carried out. Experiment and application ana is done to analyze the WSN node’s performance.