Abstract
Wireless sensor networks (WSNs) consist of smart nodes that observe a phenomenon of interest (POI) via several sensors. They are extensively used in environment surveillance and can be fit very well in fire detection where detecting fire correctly in real time while avoiding false alarms is crucial. Detection in each node is carried out by fusing the data of the sensors connected to that node. In this paper, a data fusion scheme is proposed in which the measurements of temperature and relative humidity sensors are fused while the correlation among them is resolved using the copula theory. The proposed scheme is validated using a practical data set.
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