The Design And Implement Of Emergency Escape Guiding Algorithm Based On Zigbee Networks

Traditional fire alarm systems only have functions of disaster monitoring and alarm, but there are no functions of escape guiding. Trapped people in the building are always disable to find a correct path for escape quickly and thus cause the loss of life and property. It is possiblefor using WSN to emergency guiding because of the development of WSN technology.This paper proposed a 3D emergency escape guiding algorithm based on Zigbee Networks (3D-EEGA). Take fire for instance, sensor nodes are used for monitoring the smoke and temperature that can identify a fire. The node that detects a fire will broadcast an emergency message, and the other nodes that receive the emergency message will compute a best escape route by a distributed algorithm. People will escape from the disaster areas by these routes. Each node will also update its guiding direction to adapt to the new situation of disaster. The algorithm we proposed has five main characteristics as below:(1) The nodes’ initial directions that have the same function as the traditional emergency guiding instrument are used to guide people at the absence of disaster.(2) All nodes will compute safe guiding directions quickly and exactly and form escape routes collaboratively when disaster happens.(3) Every node will change the guiding direction and route according to the location of disaster when disaster spreads.(4) Nodes that are close to disaster will compute their guiding directions at an earlier time.(5) Between floors can also get the best guiding in 3D-building when computing the escaperoutes.We simulate the algorithm to validate the correctness of guiding directions and the adaptability of various buildings. By comparing to the guiding algorithm proposed by Zhang shows that our algorithm is more suitable for 3D-building environments. Finally we apply this algorithm to real environments and validate it. By analyzing the experimental results validates the feasibility and correctness of the algorithm in real environments.