## 4 Fire and Firefighter Monitoring  
### Fire Monitoring  
The objective is to keep at the Base Station updated information on the status of the fire. Measurements of the current fire and smoke status are critical to plan fire fighting. In fact, smoke inhalation is the main death cause among fire victims. Poisoning due to toxic components or small solid particles clogging the pulmonary alveoli can result in victim suffocation.  
All nodes are equipped with suitable sensors to measure temperature and concentrations of \(CO_{2}\), \(CO\), hydrogen and hydrocarbon gases. \(CO_{2}\) is one of the main products of combustion and it is dangerous in high concentrations. \(CO\) is a colorless and odorless very toxic gas produced by partial combustion when there is not enough oxygen to produce \(CO_{2}\). In addition, in many cases, such as industrial fires, special attention should be devoted to the monitoring of highly flammable gases such as hydrogen or hydrocarbon gases. In the system prototype implementation, we selected _Figaro TGS4161_  
Figure 1: (**Left**) Prototype of the mobile nodes used in the experiments; (**Right**) Photograph taken during the validation experiments.  
and _TGS5042_ models as \(CO\) and \(CO_{2}\) sensors, respectively. Also, we used model _Figaro FCM6812_ sensor, which provides an estimation of the flammable gas concentrations adding the contribution of hydrogen, methane, butane and propane.  
Sensors selected for our system are suitable for integration due to their low size and consumption. However, they should be calibrated to improve accuracy. The gas concentration sensors were calibrated using a high performance gas measurement equipment _TESTO T350 XL_, capable of accurately measuring the concentrations of \(CO\), \(CO_{2}\) and hydrocarbon gases, among others. The surface-mount device (SMD) temperature sensor of _TelosB_ nodes was also tested. Temperature measurements of two nodes at 3 m and 5 m from a fire machine were registered, see Figure 2. Temperature raised and relative humidity dropped as soon as the fire started at time \(t=1,280s\).  
Each node periodically gathers measurements from its sensors and forwards them in _FireSense_ packets to the Base Station using dynamic multi-hop WSN routes. The information contained in these packets includes a packet identifier, an identifier of the sender node and the concentrations in parts per million of \(CO\), \(CO_{2}\) and hydrocarbon gases. Measurement and packet transmission rates are configurable. High frequencies can improve monitoring updating and compensate packet loss, but also can increase network traffic. In the experiments carried out, packet transmission was set in the range 5-15 s, sufficient to cope with indoors fire spread rates [18]. For efficiency and scalability, _FireSense_ packets use unconfirmed transmission. We prefer losing some data packets rather than adopting confirmed transmission protocols that can greatly increase network traffic with packet acknowledgments and retransmissions.  
_FireSense_ packets are routed to the Base Station using multi-hop channels computed using the widely proven Collection Tree Protocol (CTP) algorithm [19]. CTP is an efficient multi-hop routing protocol for transferring data from one or more sensors to one or more root nodes. CTP relies in Link Quality Estimators to dynamically select the route and can quickly adapt to the changes in the network. Adaptability is particularly interesting in our problem, where node failure is not unusual. Also, CTP is efficient in the sense that it includes mechanisms that do not require too much communication among the nodes. Notice that the CTP can start while the nodes are still being deployed, which minimizes delays.  
Figure 2: Temperature and relative humidity measurements obtained from two nodes at 3 m and 5 m from a fire machine.