# Thermal, Multispectral, and RGB Vision Systems Analysis for Victim Detection in SAR Robotics
## Appendix 1```
## 5 Conclusions

In the context of this study, it is deduced that the spectral ranges of light with the most significant impact on the detection of victims are primarily Green (GRE), Red (RED), Near-Infrared (NIR), and Infrared. Regarding the former two, their significance lies in their substantial contribution of environmental information. On the other hand, the latter two are noteworthy for their ability to capture information that eludes human visual perception. The comparative analysis undertaken for victim detection across three spectral ranges has facilitated the identification of key parameters with varying degrees of impact on system precision. Notably, \(\theta\) (indicating a totally covered victim), \(\beta\) (corresponding to poor light conditions), and \(\epsilon\) (indicating the presence of heat sources) have emerged as influential factors significantly affecting victim identification. In contrast, \(\tau\) (associated with changing light conditions) and \(\gamma\) (with indoor settings) exhibit minimal impact, independent of their respective parameters, in identifying victims with either type of camera. The prominent influence of these identified factors accentuates the critical importance of careful consideration and optimization during system design. Regarding thermal imaging dominance under low-light conditions, these images outperform RGB and multispectral methods in victim detection, leveraging their reliance on thermal footprints. The method detects individuals hidden by slender obstructions, demonstrating superior obstacle penetration compared to RGB-based techniques. As thermal imaging relies on a single measurement spectrum, Multispectral's broader spectrum combinations enhance its adaptability and robustness in diverse scenarios. Additionally, the Multispectral method demonstrates robust detection in challenging conditions, such as scenarios involving less distinctive clothing, where RGB methods face limitations. In scenarios with heat sources or incidents like fires, the combined use of RGB and Multispectral methods offers a substantial advantage, surpassing the performance of the thermal method. As prospective avenues for future research, exploring potential novel indices could be contemplated through integrating the diverse bands captured by the three types of sensors. These indices could be iteratively generated through repetitive loops, leveraging their operational versatility as matrices. Alternatively, optimization and error minimization techniques, facilitated by machine learning, could be applied to extract distinguishing elements from the new images. This approach aims to assess their relevance in the detection of victims. Conceptualization, A.B., C.C.U., D.O. and J.d.C. ; methodology, A.B. and C.C.U. ; software, C.C.U. and D.O. ; validation, C.C.U. and D.O. ; formal analysis, C.C.U. and A.B. ; investigation, C.C.U., A.B., D.O. and J.d.C. ; resources, A.B. and J.d.C. ; data curation, C.C.U. and D.O. ; writing--original draft preparation, C.C.U., D.O. and J.d.C. ; writing--review and editing, C.C.U., A.B. and D.O. ; visualization, A.B. and J.d.C. ; supervision, A.B. and J.d.C. ; project administration, A.B. and J.d.C. ; funding acquisition, A.B. and J.d.C. All authors have read and agreed to the published version of the manuscript. * [PERSON] and [PERSON] (2020) [PERSON]; [PERSON] Investigation of the Challenges and Their Best Practices for Post-Disaster Reconstruction Safety: Educational Approach for Construction Hazards. In Proceedings of the Transportation Research Board 99 th Annual Conference, Washington, DC, USA, 12-16 January 2020. * [PERSON] et al. (2003) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Test arenas and performance metrics for urban search and rescue robots. In Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03 CH37453), Las Vegas, NV, USA, 27-31 October 2003 2003; Volume 4, pp. 3396-3403. * [PERSON] et al.