Data Mining Techniques Applied to Wireless Sensor Networks for Early Forest Fire Detection
Refereed Conference Meeting Proceeding
Nowadays, forest ﬁres are a serious threat to the environment 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 corresponding 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 experiments, we show that our approach can provide a fast reaction to forest ﬁres while consuming energy eﬃciently.
IEEE International Conference on Communications (ICC’2016
Digital Object Identifer (DOI):
National University of Ireland, Dublin (UCD)
Open access repository: