## 1 Introduction  
Thousands of urban and industrial fires occur each year leading to the destruction of buildings and infrastructure. Fire fighting mobilizes important resources and is a very dangerous activity, which originates many casualties every year. In most cases, the lack of information on the evolution of fire and the conditions the first responders are exposed to plays an important role in these accidents. Traditionally fire status is visually estimated by skilled firefighters. In many cases, human perception errors have led to wrong decisions. Various systems have been developed using sensors (such as GPS,thermoders, gas concentrations sensors and visual/infrared cameras) carried by firefighters. The measurements and images gathered are transmitted to a monitoring and command station, where fighting decisions are taken. Most of these solutions use single-hop communications, which are affected by limited transmission ranges. To cope with it, the communication systems used by fire brigades use low frequency bands to allow longer ranges. Even in this case, the transmission range can be insufficient in complex environments, such as large buildings and basements. In addition, if firefighters are indoors, GPS will be inoperative, and the lack of information on firefighter location can lead to accidents.  
In recent years, different network communication technologies have appeared. WSN are comprised of a large number of nodes with sensing, computing and wireless communication capabilities that organize themselves in networks. Low size, cost and energy consumption are among the main features of WSN technology. Despite the simplicity of single WSN nodes, cooperation provides WSN with high flexibility, robustness and tolerance to failures. These features together with battery-based power, minimal invasion and flexible deployment have motivated the extension of WSN technologies to a growing number of applications [1]. The use of WSN in fire applications has attracted interesting research efforts. However, despite the variety of approaches and methods, very few of the reported systems have been experimentally tested.  
This paper describes a WSN tool for fire-fighting activities. It integrates the following functionalities: fire monitoring, firefighter monitoring and dynamic escape path computation. It also includes a robust localization method that employs RSSI-range models dynamically trained to cope with the peculiarities of the environment. The safe escape method is based on guiding: the path information is distributed in the WSN. The Base Station uses optimization tools to periodically compute minimal cost paths using updated fire measurements. These functionalities have been experimented in physical settings. Furthermore, a prototype of the proposed system has been validated in close-to-operational conditions. This paper describes the functionalities, protocols, implementation and experimental results.  
The organization of the paper is as follows. Related work is briefly described in Section 2. The general description of the proposed system is in Section 3. Section 4 presents the techniques for fire and firefighter monitoring including the training-based localization method. Section 5 describes the dynamic escape path computation. Partial and validation experimental results are in Section 6. Conclusions and future work are described in the last section.