## 6 Conclusions  
This study selected and evaluated abnormal situation detection services based on thermography cameras, which enable facile detection of objects at night, and the identification of early signs of dangerous situations according to temperature changes in heat; the goal was to overcome the limitations of CCTV images, which is the current main tool. We conducted in-depth interviews with experts to select abnormal situation detection services based on thermography cameras. We also suggested an integrated Fuzzy AHP/TOPSIS model, which induces a more reasonable selection to support the decision-making of the demand for introducing thermography cameras. We used this model to evaluate our proposed service model and then conducted a comparative analysis of preference differences between developers and local governments.  
Our main findings are as follows. The analysis results of all respondents indicate that services related to traffic accident prevention, which threaten pedestrian safety at night when CCTV video monitoring is not effective, had the highest evaluation. This is in the context of previous research, such as day and night pedestrian detection on the road and autonomous-driving-related object detection [19; 20; 21; 32]. Meanwhile, services related to nighttime crime prevention ranked the lowest. This is because it became easier to detect objects at night due to the higher illuminance performance of newer CCTV for crime prevention, while more traffic accidents have happened due to pedestrians in dark clothing and dark vehicles at places with insufficient road lighting. Pre-fire phenomenon detection services inside buildings, facilities, and forests also ranked high, as the identification of pre-fire phenomena can help avoid larger disasters. The comparison of analysis results of developers and local governments' operators shows that developers highly evaluated temperature changes in heat, which is the core principle of thermography cameras. This was particularly understandable by their preference for the detection service of the pre-fire phenomenon. This is consistent with previous studies of such areas as fire propagation, volcanic monitoring, and building thermal bridge diagnosis [22; 40; 41; 42; 43; 44; 46; 47]. Meanwhile, local governments highly evaluated the controlling situations related to citizens' safety within the thermography camera service area. Service decisions must consider the opinions of both developers with a high understanding of technology, and operators who actually introduce and manage services.  
This study contributes to the literature and provides the basic foundation for the development of services utilizing thermography cameras by presenting thermography camera-based abnormal situation detection services and selection methods. Importantly, our study considers involving both developers and operators in decision-making when using sensors. We expect that the effectiveness and practicality of services using thermography cameras will further increase through future studies, such as those on spatial analysis, service implementation plans, and test bed demonstration. Together, these efforts can result in a stronger social safety net that allows citizens to lead safe lives.  
Conceptualization, W.C.; methodology, W.C., B.J. and I.J.; software, W.C. and H.S.; validation, B.J. and I.J.; formal analysis, W.C. and Y.J.; investigation, W.C.; resources, W.C.; data curation, H.S. and Y.J.; writing--original draft preparation, W.C.; writing--review and editing, W.C.  
and B.J.; visualization, W.C. and I.J.; supervision, W.C.; project administration, W.C. All authors have read and agreed to the published version of the manuscript.  
Research for this paper was carried out under the KICT Research Program (project no. 20230117-001) funded by the Ministry of Science and ICT.  
Not applicable.  
The authors declare no conflict of interest.