# Design of a Mixed Reality System for Simulating Indoor Disaster Rescue
## 4 Experimental Results  
This section describes the system environment and performance evaluation. The proposed MR system uses Unity, as stated above, which can handle VR/AR systems. Tables 1 and 2 list the specifications of the MR system and device, respectively. Time is the most crucial factor when rescuing survivors. Five minutes is the golden time to rescue survivors of indoor disasters such as fires, [5] as >60% of fire deaths are caused by suffocation due to gas and smoke [34]. Therefore, the goal in our simulations is to rescue victims within 5 min. A total of ten experimenters (eight men and two women) participated in our system evaluation based on this time limit; three had experienced MR environments (VR or AR) at least once while the other seven had no experience with these environments. Rescue operations in real-world disaster environments involve many complex variables. In virtual disaster environments, rescue operations can be simplified. \begin{table}
\begin{tabular}{c c} \hline \hline  & **Laptop** \\ \hline CPU & AMD Ryzen 9 5900H 3.30 Hz \\ \hline RAM & 16 GB \\ \hline OS & Windows 11 Pro \\ \hline GPU & NVIDIA GeForce RTX 3060 \\ \hline Tool & Unity 2020.3.35 LTS \\ \hline Framework & MRTK 2.7.3 \\ \hline \hline \end{tabular} \(\mathcal{C}\)PU: central processing unit; RAM: random access memory; OS: operating system; GPU: graphics.  
\end{table} 
Table 1: Mixed reality system specifications. Figure 15: Movement toward another exit. Thus, the golden time of 5 min was reduced to 2 min for the rescue simulations. The reason for setting it to 2 min is that there are many situations when rescuing people from a real disaster site. For example, you may find a person, but there may be obstacles in front of you that need to be removed, or there may be a fire that needs to be extinguished. If we had designed the system to take this into account, we would have set the experiment time to match the prime time slot, but as we designed the system to simply rescue people by touch, we assumed that it would take 1 min and 30 s to remove the obstacle or extinguish the fire, so we set the experiment time to 2 min. Each experimenter supervised one experiment for each scenario (total of three experiments). We evaluated the performance of our MR system by recording the time it took participants to rescue the victim/s and escape. The evaluation indices for the scenarios are listed in Table 3; S1-S3 focus on speed, accuracy), and the ability to handle unexpected situations, respectively. Figure 16 shows the average escape times for the three scenarios. The final participants to complete the experiment were asked to provide feedback to guide future research aimed at system improvements. In S1, rescue and escape were achieved with a reduction in the golden time of 39.3%, indicating that the navigation guidance provided by the system can enable the rapid rescue of victims and subsequent escape to safety of the rescue. In S2, the golden time reduction was 11.9%. Finally, the golden time reduction was about 20.6% in S3. Thus, the re-exploration time required for escape following an unexpected situation was reduced. The mean reduction in golden time was 23.9%. Thus, the MR system facilitated indoor disaster rescue. Ways to potentially improve the prototype system are summarized in Table 4 based on participant feedback. Based on the participants' feedback, support for multiple devices should be the top priority for MR system improvement. In the system verification stage, an individual standing next to the person wearing the equipment interacted with the virtual objects by hand. We hope to improve the system such that it can be used in conjunction with many MR-compatible devices. Other suggested improvements included addressing overlap of virtual objects, improving rescue operations, and minimizing spatial position error.