## 3 Service Model Selection  
In this study, the actual sources of demand are local governments' Smart City Integrated Operation Centers, which operate CCTVs and IoT sensors that can monitor citizens' life safety, and facility operators, who manage individual buildings and facilities. As mentioned before, South Korea operates Smart City Integrated Operation Centers in 226 local governments. To practically set an operatable service model, we created a group of five experts including public officials who were in charge of the control center of the local government and had experience in operating thermal cameras, and thermography image analysis developers. We also conducted a Focus Group Interview (FGI) to set alternative service models based on the expert group's opinions. FGI can be utilized when limited literature is available and solutions with new perspectives are required [81]. Especially, FGI is a highly useful decision-making support method when comprehensive perspectives and insights in diverse fields are needed [3]. In the first half of the FGI, we reviewed thermal camera-based research and application cases prepared by the authors and then focused on discussing available services to be targeted particularly with thermography image analysis developers. The thermal-camera-based research case included not only the results of prior studies of such issues as \"1-3\" fire sessions, night objects, road/traffic fields, and urban control but also examples of the actual operation of thermal camera products in the field. The main discussion topics were fire and abnormal weather control services using nighttime object detection and temperature differences. Afterward, we classified specific services while targeting the living SOC (Social Overhead Capital), which is controlled by public servants in charge of control centers of local governments. We also derived detailed services based on thermography images that can supplement existing CCTV control in road, pedestrian safety, facility management, and disaster prevention. In the second half of the FGI, we organized stratification and specific control details for the discussed service models. The final derived service model determined by the FGI was as follows. In the major classification, we derived items related to anomaly detection, such as objects, roads, facilities, and disaster prevention situations. First, we discuss the potential object anomaly detection service. In terms of its medium classification, the preventive detection service of traffic accidents at night includes the nighttime pedestrian detection service, identifying which can be challenging using nighttime CCTVs as well as for vehicle drivers. This classification includes nighttime mobility detection services to prevent high-risk accidents in alleys due to kickboards, and bicycles. The night security incident detection service encompasses the violence-related incident detection service (e.g., crowding, collision, and collapse), detection service for fear of crime related to violence (hereafter, \"crime fear\"; e.g., loitering and following), and intrusion status detection service at night (e.g., private land and prohibited facilities). The pedestrian hazard detection service includes the detection of dense pedestrian situations within pedestrian spaces (e.g., alleys and pedestrian paths), and a service for computing population clustering at festivals and crowded events. Second, the road anomaly detection service includes the following. The road weather hazard detection service includes a road surface temperature detection service for detecting the road surface status and abnormally high temperatures of underground facilities due to high temperatures in summer, as well as a road flooding detection service (e.g., heavy rain and drain blockage on roadside) and road ice detection service in winter. The road surface hazard detection service encompasses a road pothole detection service to detect road damage risks, such as potholes and cracks, and fallen objects on the road.