# Smart Disaster Response in Vehicular Tunnels: Technologies for Search and Rescue Applications
## 5 Discussion
The first response is the detection of the accident through the pre-installed IoT sensor, the second correspondence is the acquisition of the smoke image by the robot, and the third correspondence is the position tracking of the firefighters. As a result, since there are three ways to cope with a fire, even if one response fails, sufficient search and rescue can be completed in the remaining responses. * Cooperation with tunnel facilities. In the event of a fire, CCTV, radar, and IoT sensors first detect and report the danger, but the operation of related facilities for further response is controlled by using the disaster prevention equipment built into the tunnel. Typically, there are ventilation fans that remove smoke, radio equipment that broadcasts emergency announcements, and barriers that prevents the entry of additional vehicles into the tunnel. In particular, the ventilation fans must discharge smoke to the exit on the opposite side of the entrance where the fire brigade enters. However, it is important to maintain the speed of the ventilation fans below the critical speed at which the fire can spread. Figure 20 illustrates the concept of the operation of a ventilation system and the entrance direction for fire fighters. * Future investigations. In this system, we propose a countermeasure based on three technologies, IoT, robots and localization, in case of a fire in a motor way tunnel. However, due to the nature of the fire, the rate of temperature increase and the direction of smoke diffusion, and evacuation routes may vary depending on the type and structure of the tunnel. For example, the width, height, slope, and degree of curvature of a road can directly affect the fire, and the effectiveness of fire facilities, including ventilation fans, is also significantly affected after a fire. In addition, when the proposed equipment uses wireless communication, unexpected signal distortion, attenuation, interference, disconnection and so on may occur due to high temperature and internal obstacles. To overcome these problems, it is necessary to provide quick data collection, analysis, and decision-making on the latest fire as well as on-site environmental analysis. Future research \begin{table}
\begin{tabular}{c c c} \hline \hline
**Time (sec)** & **Operation Step** & **Category** \\ \hline \hline Usual & Continuous monitoring via IoT sensors, Radar, CCTV & \\
00:00 & Fire occurs & \\ \hline
00:10 & Fire detection via IoT sensors & \\
00:20 & Tunnel supervisor confirms the accident via video data & \\
00:30 & Supervisor reports fire station and transmits related data & 1 st response \\
00:40 & Fire station confirms the fire data via Internet & \\
00:50 & Fire fighters also confirm the data in the fire truck & \\ \hline
01:00 & Road patrol arrives at the site & Conventional \\ \hline
01:20 & Road patrol uses UGA/UAV for further search operations & 2 nd response \\ \hline
04:00 & Road patrol start to rescue operations & \\ \(\
eg\)- & Tunnel supervisor controls ventilator, pump and etc. & Conventional \\
10:00 & Fire fighters arrive & \\ \hline
10:30 & Fire fighters use UGA/UAV for further search operations & 2 nd response \\
13:30 & Fire fighters set up strategy for rescue using robot’s data & \\ \hline
13:40 & Fire fighters enter the tunnel (real time localization) & \\
18:30 & Ad hoc networking during the rescue operation & 3 rd response \\
25:00 & Response finished & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Operation scenario using proposed system. Figure 20: Cooperation with ventilation system. directions are to introduce artificial intelligence and big data-based analysis technology to solve these uncertainties.