Distributed Event Detection in Wireless Sensor Networks for Forest Fires

As the technology is advancing, Wireless Sensor Networks (WSN) is a gaining importance in recent research areas as it has proved its usefulness in warning disasters and save lives and assets. When an unusual event is noticed in the networks, an event is detected through the sensor devices placed at distributed locations. This event detection information is passed to the base station and intelligent decision is taken. Various machine learning techniques are used to decide whether the event has occurred or not. In this paper, we proposed an ensemble distributed machine learning approach for detecting events. This approach works in two phases, base phase and meta phase, clustream and Support Vector Machine approach are used for detection and prediction of events. One hop tree is used in this approach in order to minimize the delay in transmitting information.