M.S. Obaidat, J.L. Sevillano, and J. Filipe (Eds.): ICETE 2011, CCIS 314, pp. 43–59, 2012. © Springer-Verlag Berlin Heidelberg 2012 A Wildfire Prediction Based on Fuzzy Inference System for Wireless Sensor Networks V.G. Gasull 1 , D.F. Larios 1 , J. Barbancho 1 , C. León 1 and M.S. Obaidat 2 1 Department of Electronic Technology, University of Seville, Seville, Spain 2 Department of Computer Science & Software Engineering, Monmouth University, W. Long Branch, NJ 07764, U.S.A. {vgasull,dflarios}@dte.us.es, {jbarbancho,cleon}@us.es, obaidat@monmouth.edu Abstract. The study of forest fires has been traditionally considered as an impor- tant application due to the inherent danger that this entails. This phenomenon takes place in hostile regions of difficult access and large areas. Introduction of new technologies such as Wireless Sensor Networks (WSNs) has allowed us to monitor such areas. In this paper, an intelligent system for fire prediction based on wireless sensor networks is presented. This system obtains the probability of fire and fire behavior in a particular area. This information allows firefighters to obtain escape paths and determine strategies to fight the fire. A firefighter can access this information with a portable device on every node of the network. The system has been evaluated by simulation analysis and its implementation is being done in a real environment. Keywords: Fuzzy System, Wireless Sensor Networks, Forest Fire, Simulation. 1 Introduction Usually, a wireless sensor networks is composed of multiple nodes spatially distri- buted in an area. These nodes obtain information on the environment such as tempera- ture, pressure, humidity or pollutants, and send this information to a base station. A wide variety of applications for such networks often apply some kind of supervision, event detection, tracking or control, among others [1]. In [2] a large-scale deployment of these networks has been used for the supervision of wildlife habitats. Most applications of sensor networks in forest fires are based on the detection of fires, such as [3] which uses a WSN based on a swarm-inspired system for detecting wildfires. Reference [4] shows an algorithm based on fuzzy logic for detecting events. In this case, the event is fire detection. The nodes are equipped with various sensors such as temperature, humidity, light intensity and carbon monoxide. In [5], a satellite monitoring system with a WSN is used to detect a forest fire. In [6] an implementa- tion scheme of communication oriented WSN and monitoring computer is presented. The work in reference [7] reduces the consumption of the transmission using the in- formation gathered by analyzing the Fire Weather Index (FWI) System. Reference [8] uses data from a WSN in the FARSITE simulator for fire detecting.