## 2 Related Work  
WSN have been proposed for the automatic detection of forest fires. Traditional technologies rely on visual cameras at static locations [2] or combined with Unmanned Aerial Vehicles [3], among others. WSN provide ubiquitous detection capabilities for forest fire. In [4], a system consisting of sensors (thermo and radiation with GPS) carried by animals living in the environment is used for forest fire detection. In [5], the design and development of a WSN involving sensors and IP cameras is described. In [6], fire detection is modeled as a k-coverage problem. In [7], a WSN with nodes equipped with temperature and humidity sensors were used to detect fire and extract measurements of the fire spread. WSNs have also been proposed for forest fire monitoring. FireWxNet consists of a WSN designed to report weather conditions as well as images in fire environments [8]. The paper shows real deployment of the WSN, which is evaluated in terms of battery performance and information gathered. Despite these efforts, WSN technology still has not solved issues such as the costs of maintaining thousands of nodes deployed in forest areas and their potential pollution. WSN have also been proposed for detection and monitoring in urban and industrial fires. In [9], a WSN-based fire detection system was proposed to ensure safety of the people working in mines. [PERSON] _et al_. proposed an innovative framework for residential fire detection [10]. They introduced metric of interval-message-ration (IMR) and evaluated their framework using the IMR metric. In [11], a WSN-based fire detection system for large buildings is presented. It is based on dense deployments of sensor nodes that periodically check temperature/smoke concentration and report these values to a surveillance center through WSN channels. Significant efforts have been carried out to improve WSN detection and monitoring. In [12], the authors proposed the use of machine learning techniques to improve fire detection and false alarm rejection. A WSN-based system for fire monitoring based on measurements from humidity, temperature and light sensors was proposed in [13]. WSN have also been proposed for other fire fighting activities. Significant research efforts have been devoted to the computation of escape paths in emergency evacuation. Work [14] describes a distributed method in which each node is assigned with an _altitude_ value that can be seen as a degree of danger. Safe paths to exits are along sensors with high altitudes to sensors with low altitudes. The work in [15] proposes a distributed method to find safe paths to an exit through a network that can contain multiple sources of danger. Exits generate positive potentials to attract the navigating user, and obstacles generate repulsive potentials. The work in [16] uses models of the progress of the hazard and of the evacuees to ensure the evacuees stay safely ahead of the hazard. Its applicability is questionable since fire/smoke spread is difficult to be predicted and requires very complex models. Distributed guiding methods assume that nearness between nodes is related with radio hops. However, due to radio's penetration capacity, single hop neighbor nodes are not necessarily physically close. In fact, if they are in different rooms the path length can be very high. Thus, each deployed node requires having a local map of the building to prevent guiding firefighters to a dead end. Although tedious in large deployments, this assumption is feasible in permanent settings. However, it cannot be applied if the nodes are not part of the building infrastructure, as is in our problem. Despite this high variety of methods and approaches, few of the reported works have been experimented in physical settings and very few have been validated in close-to-operational conditions. This paper describes a WSN-based tool to increase the level of safety in fire-fighting activities.