## 4 Empirical Analysis
### Analysis of Alternatives from All Respondents
Equations (7) and (8) were used to calculate the normalized fuzzy decision matrix and the weighted fuzzy decision matrix. To use the evaluation of the alternative to the CCTV system for AI in the evaluation criterion of crime prevention effectiveness as an example, the upper bound (\(\mathrm{c_{i}}^{*}\)) for crime prevention effectiveness was 4.5; therefore, the decision matrix was \(\overline{\mathrm{R}}=\left(\frac{1.5}{45},\frac{3.5}{45},\frac{4.5}{45}\right)\). The weighted fuzzy decision matrix was calculated as \(\overline{\mathrm{V}}=\left(\frac{1.5}{45},\frac{3.5}{45},\frac{4.5}{45}\right) \times(0.10,0.19,\)\(0.36)=(0.03,0.15,0.36)\). Then, the FPIS and FNIS were calculated using Equations (9) and (10) (Table 8). Using Equation (11), this study calculated the distance to the FPIS and FNIS by alternative. To use the FNIS for the CCTV system for AI in the evaluation criterion of crime prevention effectiveness, it was \(\mathrm{d}(\widetilde{\mathrm{x}},\overline{\mathrm{y}})=\sqrt{\frac{1}{3}[(0.03-0.02)^{2}+(0.15-0.07)^{2}+(0.36-0.28)^{2}]}\) = 0.067. Using Equation (12), this study calculated the final distance to the FPIS (\(\mathrm{d_{i}^{*}}\)) and FNIS (\(\mathrm{d_{i}^{-}}\)) in each of the alternatives (Tables 9 and 10). Using Equation (13), this study calculated the proximity coefficient (\(\mathrm{CC_{i}}\)) and rank by alternative, which are presented in Table 11. First, this study calculated the mean of \(\mathrm{CC_{i}}\) for each of the four categories and examined the trend in the importance of the categories of intelligent CPTED systems. AI/CCTV showed the highest priority with 0.83, which was followed by IoT/lighting with 0.57, platform with 0.55, and community with 0.38. It seems that the respondents gave more priority to the elements that could be directly monitored from the perspective of controllers, such as CCTV systems, IoT, and the crime prevention system. The analysis of technology elements showed that the CCTV system for AI ranked first, with 0.93 in \(\mathrm{CC_{i}}\). Crime prevention effectiveness, economic viability, and sustainability were found to be more important than other alternatives, and policy conformity and field applicability were also considered highly important. The results seem to reflect that CCTV combined with AI, which has become a hot topic recently, may serve as a powerful tool to provide clues to solve crimes in reality. The crime monitoring system (\(\mathrm{CC_{i}}\): 0.82), which was evaluated evenly across all evaluation criteria, ranked second. The results likely reflect the value of the services from the public sector's point of view as most of the technologies and services are combined and operated based on a platform in the control centers in which the evaluators work. Moreover, the results might reflect some value in efficiency to replace the current manual monitoring personnel. AI video analysis for crime prevention (\(\mathrm{CC_{i}}\): 0.79) ranked third, which was evaluated most highly in terms of competitiveness with existing services and growth in the service sector. The results indicate that the evaluators had very high expectations for the potential of the service elements. AI video analysis for living safety (\(\mathrm{CC_{i}}\): 0.76) ranked fourth. The results seem to reflect that AI video analysis based on CCTV systems holds importance in not only preventing crimes but also ensuring living safety. This study conjectures that the evaluators selected the first to fourth ranks as the top technology elements due to their value as underlying solutions required to provide other technology elements as a service.