## 3 Results
### Experiments
#### 3.1.2 Experiments on Notification of Accidents by Major Cities in Korea  
After selecting three regions (Daegu, Gwangju, and Busan), CCTV in the area was checked, and one CCTV was selected for each region, assuming that it was AI CCTV and conducting a hypothetical experiment. A virtual experiment was conducted on the assumption that each AI CCTV had an accident in a position that could be detected. In addition, the user's location in each region was set within 5 km of the AI CCTV location. Figure 12(a)-c are pictures of abnormalities detected by CCTV at the Gundeulbawi Intersection in Daegu, Gwangcheon Bridge 1 in Gwangju, and CCTV on the Jurve ramp overpass in Busan. Assuming that the CCTV in the Daegu area is located at the Gundeulbawi Intersection and that the user is in a virtual location called Daebong Intersection, we make an assumption about the occurrence of a traffic accident at the Gundeulbawi Intersection CCTV. Daegu ranked first in the nation for the rate of traffic accidents in 2020, and the road with the most traffic accidents is the 'Shincheon-daero' road. Reverse driving accidents often occur, because the road is narrow and difficult to drive in [14]. The width of the road is rather narrow, and most of the roads are 4-6 lanes. There are many things that have not been managed smoothly, such as CCTV shaking, part of the CCTV screen being obscured by streetlights or other objects, or being affected by weather conditions such as sunlight. Because of these, CCTV, which is difficult to identify objects, is often observed, and the resolution is very poor. We assumed that the accident corresponding to the Gwangju area occurred at Gwangcheon Bridge 1 and that the user is located in the Gwangju National Museum. Gwangcheon Bridge 1 is included within 5 km from the user's location. A traffic accident video detected by AI CCTV is one of the test videos and shows the front part of the vehicle crashing. For that reason, CCTV detects an accident that occurred at Gwangcheon Bridge 1, and accident information and photos are transmitted to the user. On CCTV in Gwangju, a car accident occurred in the middle of the CCTV screen, making it easy to detect the accident. The vehicle is clearly visible, and there are no objects obstructing the view in CCTV. This helps to make object recognition easier. CCTV in Gwangju monitored a narrow area with CCTV, making it easy to detect accidents. However, if CCTV can see a large area at once, the size of the vehicle looks small, and the accident is not clearly visible, so it is not easy to detect the accident. In addition, there are cases where vehicles and roads are obscured by high-voltage lines and electric wires on CCTV showing a wide road, and there are places where resolution needs to be improved. We assumed that the accident in Busan occurred on the Jurye ramp overpass, and the user is located on Dong-Eui University Gaya campus. Since the Jurye ramp overpass is included within 5 km of the user's location, information and photos about the accident that occurred at the location are transmitted to the user. CCTVs in Busan are characterized by being located on roads where roads, tunnel road networks, hillside roads, and multi-lane roads intersect up to the sea as Gwangan Road [15]. Moreover, there are many cars on the road that suddenly change lanes, so it is not easy for drivers to drive because car accidents occur often. Although there are places where there is a big difference in resolution between CCTVs, the overall CCTVs' resolution is high. CCTV located on bridges and tunnels provides images that can easily detect vehicle accidents because the viewing angle is narrow. However, since CCTVs installed on multi-lane roads like the Yeonsan intersection have a wide angle of view, it is possible to detect an accident only by enlarging the CCTV image. As a result of carrying out an experiment using CCTV in Daegu, Busan, and Gwangju, it was found that the accuracy of vehicle accident detection results increased in CCTVs with high resolution and a narrow angle of view.