The Effectiveness of Crime Prevention Using GIS Technology and CCTV Application for Smart City

The closed-circuit television (CCTV) surveillance cameras are often credited for reduction of crime pattern especially in metropolitan area. CCTV is a surveillance system using video cameras and related equipment as normally used in business premises, commercial areas and in high-risk areas of crime to private residences. Some of CCTV equipped with artificial intelligence (AI) face recognition system which make it more effective for crime awareness and prevention. In this chapter, the focus is on examining the correlation between crime patterns and factors that influence the installation of CCTV cameras, specifically transitioning from “pre” to “post” indicators. The CCTV system used in this study includes the normal CCTV and also the one that equipped with AI face recognition. For this study, GIS analysis tools, including Optimized Hot Spot Analysis (OHSA), were utilized to identify crime patterns, while a regression model of Ordinary Least Squares (OLS) was used to identify the relationships between CCTV installation and crime patterns. Through the application of these analysis tools, it was discovered that CCTV operation is correlated with a significant reduction in crime incidents. Given a Koenker (BP) p-value < 0.05 of 0.003, the significance of the non-stationary/not consistent CCTV impact explained was only effective in small areas and in most other areas in the study areas. Exploratory variable model for CCTV indicators contributed 43% (R2 = 0.43) variance change in incident of crime rate [F (3.39) = 11.751146, p < 0.01)]. For AI face recognition CCTV installation on one of the study area, we found that there is a significance number of the crime reduction and awareness among the community in the targeted block. But there is an evidence of spatial crime displacement to other block beyond observation. This study holds valuable significance in terms of encouraging government and law enforcement organization to prioritize safety measures and mitigate risks in urbanized areas with high crime rates. Its findings aim to promote the concept and vision of smart cities, fostering a safer environment for the urban population.