Abstract

Wireless Sensor Network (WSN) is highly demanded in the field of networking. This popularity of WSN is because of its ability to yield the real time sensory data. This sensory data is further processed to generate useful and sensible results required for an application. The natural disaster detection and management is the main focus behind this proposed project. Natural critical event contributes a large penalty in terms of big loss of living and nonliving asset. In this paper, we proposing an algorithm that, (1) detects the critical event under WSN, (2) calculates direction of growth and speed of the critical event, (3) predicts the next affecting area within anticipated time period. (4) Alerts the prevention system around the WSN. Wireless sensor network is generating the real time data such as temperature, pressure, ambient light, humidity etc. We use this data as an input to the system. The power of computation is applied on the sensory data to make the system functioning as per desire. In this paper, we proposed a predictive algorithm for a critical event detection and management. A prevention system is a set of preventing objects. The algorithm predicts critical event probable spread area and accordingly give alert to all preventing objects. These preventing objects are responsible to take a contrary action against calamity. WSN is programmed to give a activation signal to all those prevention systems or objects which are under critical event probabilistic area. In this way, we can manage the critical event and reducing amount of losses considerably.

Authors and Affiliations