Intelligent data classification and aggregation in wireless sensors for flood forecasting system

Abstract

Flood is a major natural hazard in the world. For the period 1996-2005, about 80% of global natural disasters were meteorological or hydro. The floods have affected an average of 66 million people per year between 1973 and 1997. By these statistics, floods are considered the disasters that produce the most damage. Thats why we must handling floods data with great caution since human life is at stake. In this paper, we present an intelligent model that gathers data received from the wireless sensors and reach them in an intelligent way on one hand, on the other hand, it detects erroneous or redundant data to classify them to just have reliable and adequate data to be stored in the database in order to be processed in the decision support system for real time flood forecasting by using of the multi-agent system (MAS) to process data, eliminate redundancy, non-useful and erroneous data and establish collaboration between mobile agents to send the results to the base station.