Data Mining Techniques Applied to Wireless Sensor Networks for Early Forest Fire Detection

International audienceNowadays, forest fires are a serious threat to the environ- ment and human life. The monitoring system for forest fires should be able to make a real-time monitoring of the target region and the early detection of fire threats. In this paper, we present a new approach for forest fire detection based on the integration of Data Mining techniques into sensor nodes. The idea is to use a clustered WSN where each sensor node will individually decide on detecting fire using a classifier of Data Mining techniques. When a fire is detected, the cor- responding node will send an alert through its cluster-head which will pass through gateways and other cluster-heads until it will reach the sink in order to inform the firefighters. We use the CupCarbon simulator to validate and evaluate our proposed approach. Through extensive simulation ex- periments, we show that our approach can provide a fast reaction to forest fires while consuming energy efficiently