## 6 Application Example
### Analysis of the System Design  
In order to illustrate how to use these system models to determine the expected capabilities and limitations of a possible implementation, let us consider the proposal presented for the Once Station (Figure 8). There we can see two subsystems: the ICT infrastructure deployed in the train station and the infrastructure used to support the response process. The first one considers dedicated and stable links to support interactions among the _regular sensors_ (_i.e._, surveillance cameras and smoke  
Figure 8: Model of a simple IoT-based system to support emergency response processes. detectors), a _human data input_ (_i.e._, the activator of the alarm system), an _actuator_ (e.g., the public address system -PA system), the _processing unit_ (_i.e._, the system that diagnoses hazardous events), the _HBS_ working in the train station (e.g., security guards that are part of the permanent personnel), and a _witness unit_ (_i.e._, the local information repository). The security guards and the diagnosing system can update on-demand the information shared through the LIR. The second subsystem considers unstable links (e.g., WiFi-based networks) that support the interactions among the _HBS_ (_i.e._, the incident commander, police officers, paramedics and team leaders), _mules_ (e.g., some rescuers) and the _local information repository_. The incident commander and the paramedics exchange, according to their role, the information with the LIR. In this analysis we are going to focus only on the second subsystem, because it has more uncertainty and space for improving the information flow and availability. In order to make a more effective analysis of these features of the system design, we used an already extended version of the NS-3 simulator [39] that implements the types of nodes considered in a HWSN. We model the Once Station as a square area of \(200\times 200\) m, where 43 nodes were deployed: ten (firefighters) team leaders, one incident commander, ten paramedics (one per ambulance), twenty police officers (because they use small units) and two firemen acting as mules. We considered stationary nodes to represent the incident commander, police officers that isolate the affected area, and paramedics assisting people at the emergency place. The team leaders performing the search-and-rescue activities followed a RPGM mobility pattern [40] and they have medium mobility according to the guidelines given in [41]. High mobility was set for mules (firemen), who followed a predefined path to interconnect the team leaders with the incident commander. We considered a HWSN based on WiFi (IEEE 802.11 standard) without infrastructure, particularly an oppnet. The effective communication rage of a node was set to 30 m, that is an average value that we can obtain in open areas with obstacles (like a train station), considering to have a minimum bandwidth of 50 Kbytes for information exchange. The routing protocol used on the oppnet was Optimized Link State Routing (OLSR) [42], and all communications were performed using one or two hops. The HBS generated a message per second, which contained a piece of information of 2 Kbytes. All pieces of information were unique. Every node intended to deliver its messages through the network immediately after they were created, and the destination node was always the LIR. In these simulations we have assumed that all nodes are similar among them in term of their technical features and computing capabilities. Particularly, the node model corresponds to the features of an i-Phone 4. Fifteen simulations were done for each scenario and eight of the most representative simulations were selected for the posterior analysis. Table 1 summarizes the simulation parameters and Table 2 indicates the parameters used for the mobility models of each node type.