## 4 Empirical Analysis  
### Analysis Overview  
We evaluated the preferences for abnormal situation detection services based on thermal cameras by utilizing the integrated Fuzzy AHP/TOPSIS model. Groups of 25 experts, including persons operating local governments' control centers (12 experts) and Thermography/IR image analysis developers (13 experts), were interviewed to evaluate service models more professionally and practically. Since evaluators are experts who develop and operate practical services, they understood this study and the questionnaire very well, resulting in higher reliability of the analysis results. Furthermore, we could conduct a comparative analysis of the service preferences of providers (developers) and consumers (local governments), as well as the overall service model evaluation. In AHP research, even if the number of respondents is small, the sample size is not a problem if expertise and logical consistency are assumed [82]. We utilized Microsoft Office Excel 2019 as an analysis tool. Stratification, one of the important tasks of AHP analysis, requires an organic design of decision-making details, or evaluation criteria and hierarchical structure between alternatives, to achieve the final goal [3]. The goal of this study, which is the first class, is the selection of abnormal situation detection services based on a thermography camera. The evaluation criteria for evaluating alternatives can be classified into the second and third classes. Finally, evaluation alternatives that belong to the fourth class are the 21 service models selected previously. This study reviewed the main public guidelines that evaluated the value of technologies and services in Korea to select evaluation criteria for the second and third classes. Reviewing the Smart City Service Certification System [83], Technology Assessment of Technology Guarantee Fund [84], and Technology Value Evaluation Manual of the Ministry of Land, Infrastructure and Transport [85] shows that common evaluation criteria include compliance, technology, marketability, and business feasibility according to the evaluation purpose. This study was conducted at the stage of establishing service models before operating actual technologies and services. Therefore, we excluded items such as the degree of rights, business feasibility, and functional evaluation necessary at the project implementation stage among the previously investigated items. Three major classification evaluation criteria were finally selected: purpose compliance, service suitability, and service feasibility. Among minor classification evaluation criteria, we identified basic technology/service evaluation items and set new evaluation criteria (e.g., CCTV replacement/complementary effects) appropriate for this study (Table 3). Specifically, purpose compliance consists of the prevention of life safety, CCTV replacement/complementary effects, and conformity to \begin{table}
\begin{tabular}{p{128.0 pt} p{128.0 pt} p{128.0 pt}} \hline \hline
**Major Classification** & **Medium Classification** & **Minor Classification (Service Model)** \\ \hline C-1. Building status detection & C-1-1. Detection of building exterior damage & C-1-2. Building structure diagnostics \\ \cline{2-3}  & C-2. Detection of precursor fire events in facility & C-2-1. Detection of precursor fire events within buildings \\ \cline{2-3}  & C-2. Detection of precursor fire events in facility & C-2-2. Detection of precursor fire events within facilities \\ \cline{2-3}  & C-3. Detection of facility accident signs & C-3-1. Detection of emissions in business places \\ \cline{2-3}  & C-3-2. Detection of explosives at large events \\ \hline D. Disaster prevention anomaly detection & D-1. Natural disaster prevention detection & D-1-1. Detection of precursor forest fire \\ \cline{2-3}  & D-1-2. River flooding detection \\ \cline{2-3}  & D-2. Heat island detection & D-2-1. Heat island detection \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._relevant policies.