A Wireless Sensor Network (WSN) is a network of usually a large number of small sensor nodes that are wirelessly connected to each other in order to remotely monitor an environment or phenomena. Sensor nodes use the data aggregation method as an effective tool for estimating the desired parameters accurately and trustfully. In this paper, we have applied a cellular-automata-like algorithm and an averaging consensus algorithm for fire detection and localization with sensor networks. Indeed, when fire is detected somewhere in the network, our algorithm makes aware all the nodes in the network with a very short delay. Afterwards, the algorithm estimates the parameters of the circle surrounding the fire. To simulate the fire outbreak and the reaction of the sensor network equipped with our algorithm, we enabled the data exchange between the fire simulation software FARSITE and the communication software Castalia. The results show that our method detects the fire rapidly and monitors the extension of the fire in real time. The information about the outbreak and the extension of the fire is available from every live sensor in the network, even when part of the sensors are destroyed by the fire.