## 1 Introduction
### Overview of the Existing Literature Involving WSNs.  
WSNs may potentially provide a solution to the previously mentioned requirements (1), (2) and (3). Recent advances in WSNs support our belief that they constitute a promising framework for building near real-time forest fire detection systems. Currently, sensing modules can sense a variety of phenomena, including gas temperature and relative moisture content, two essential parameters in fire detection. Sensor nodes can operate for months on a pair of AA batteries to provide constant monitoring during the fire season. Moreover, recent protocols make sensor nodes able to organize themselves into a self configuring network, thus removing the overhead of manual setup.  
The feasibility of using wireless sensor networks for forest fire monitoring is illustrated in [2,3]. Experimental results from two controlled fires in San Francisco (California, USA) were reported. The system is composed of 10 GPS-enabled MICA2 modes collecting temperature, moisture content, and barometric pressure data. The data is communicated to a base station which records it in a database and provides services for different applications. The experiments show that most of the modes in the burned area were capable of reporting the passage of the flame before being burned. The critical point is that every node crossed by the fire is irreversibly destroyed. Another approach [4] follows a similar protocol by using the same type of device, but in addition, by considering the communication between the base station and the outside (through an Internet network). A Forest fire Surveillance System was designed for mountains in South Korea [5]. The authors provide a general structure for sensor networks and provide details for a forest fire detection application. The sensor types, operating system and routing protocol are discussed. Sensor nodes use a minimum cost path forwarding to send their readings to a sink which is connected to the Internet. The data is reported to a middleware which calculates the forest fire risk level according to formulas defined by forestry service. The calculation depends on daily measurement of relative humidity, precipitation, and solar radiation. The results are recorded in a database that can be accessed by web applications through the Internet.  
Previous studies [2,3] show the capacity of the deployed WSN to detect a fire. However, after the passage of the fire, the network is partially destroyed and the data transmission cannot go on. The destroyed sensors can no longer serve, for instance to determine the direction of the fire. How to distinguish if the signal loss is a fire or a failure? It seems also difficult to envisage that after each fire it is necessary to have a campaign to replace all burned sensors. Finally, even if the previous works are a first approach, they show that the sensor destruction is a strong deficiency of the overall WSN when immersed in a fire. This must be upgraded. Finally, there is no available result demonstrating the ability of a WSN to track the kinematics of a fire i.e., the spatial and temporal movement of its reaction zone. This is indispensable in order to be able to estimate the rate of fire spread and the direction of fire propagation. These parameters are crucial not only in the rescue actions for fight during a fire but also for fire spread modeling.