## 6 Experiments
### Partial Experiments
#### 6.1.2 Dynamic Firefighter Guiding  
This section experiments the proposed firefighter guiding method in a real setting. The experiments were carried out in the _CONET_ testbed. The building map used is shown in Figure 11(c). The WSN nodes in the _CONET_ testbed are represented as circles. With this map, all rooms include at least one node and some rooms have up to three nodes. The severity of fire conditions is represented by the color of each room: darker colors mean worse conditions. The fire measurements used in the experiment were not real: they were values previously loaded in the nodes' memory. The radio transmission power of WSN nodes was reduced to allow multi-hop channels. The building can be modeled by the graph in Figure 11(a). Each vertex represents a room. Vertex 0 corresponds to the outside of the building. Each edge is associated to a cost computed with the model used in Section 5. The performance of the method with three different fire conditions was tested. At time \(t_{1}\) the sensors detected no fire alarms. In this case, the shortest paths are considered optimal. The optimal escape paths are in Figure 11(b). Each path is an ordered list of room identifiers. The last identifier is 0, the building outside. The optimal path for room 1 is {2, 3, 6, 0}. Each path can be seen as a concatenation of local guiding information containing the current room and the next room in the path. For instance, the local guiding information for the nodes in room 1 is \(LGI_{1}=(1,2)\). Then, the Base Station floods the local guiding information in the WSN in one _GuidingInfo_ packet. _SeqF_ was set to 1. Each static node received the _GuidingInfo_ packet and uploaded the guiding information. Figure 11(c) shows with arrows the guiding information at the nodes on each room of the building. Then, a robot equipped with a mobile node-firefighter-activated the Escape Guiding Functionality. Its mobile node started broadcasting _EscapeRequest_ packets. In response, static nodes transmitted _EscapeResp_ packets with guiding information. The mobile node received them and discarded packets with old count: only _EscapeResp_ packets corresponding to the last _EscapeRequest_ packet were  
Figure 10: **(Left)** Average localization error _VERSUS_ number of static nodes taken into account in the training of the RSSI-range models. Each static node contributed with 200 measurements to the training set; (**Right**) Average localization error _VERSUS_ number of measurements from each static node taken into account in the training of the RSSI-range model. The training set contains measurements from five different static nodes. considered. After this filtering, the mobile node selected one _EscapeResp_ packet using simple rules that consider their RSSI and \(SeqF\), the version of the local guiding information. The mobile node sent the guiding information to the robot through the serial interface. The robot moved accordingly following the escape paths. Figure 11: Dynamic firefighter guiding experiments carried out in the _CONET_ testbed: (**a**) building graph; (**b**) optimal paths at \(t_{1}\); (**c**–**e**) maps with resulting escape paths at times \(t_{1}\), \(t_{2}\) and \(t_{3}\); (**f**) local guiding information at times \(t_{1}\), \(t_{2}\) and \(t_{3}\). At time \(t_{2}\) the node deployed in room 3 sensed high \(CO_{2}\) concentrations. The measurements reached the Base Station, which recomputed the escape paths. Figure 12 shows the cost of the new paths and the cost of the old paths computed using the current fire conditions. The new paths achieved a significant improvement for rooms 1 and 2. Thus, new fire status recommended updating the distributing the new guiding information distributed in the WSN. Figure 11(d) shows with arrows the guiding information stored in the nodes after the new flooding. The new escape paths avoided room 3. While in \(t_{1}\) the optimal path for room 2 was {3, 6, 0}, in \(t_{2}\) it was {5, 7, 6, 0}. After a while, \(CO_{2}\) spread to rooms 2 and 6.