Smart cities require smarter crime prevention methodologies: Integrating AI within urban safety frameworks

ABSTRACT. As urban areas transform into intelligent ecosystems, artificial intelligence technologies are assuming an increasingly vital role in the prevention of urban crime. This research amalgamates artificial intelligence with conventional criminological theories, specifically Routine Activity Theory (RAT) and Crime Pattern Theory (CPT) to theorize framework and practical approaches to urban crime prevention. To methodically evaluate the convergence of artificial intelligence implementation in urban crime deterrence. AI implements predictive policing and real-time monitoring, establishing a novel kind of oversight that perpetually observes metropolitan environments, hence diminishing prospects for criminal activity. This study contends that multidisciplinary methodologies for urban crime prevention, integrating technology with social and spatial theories, yield more successful and nuanced solutions. The findings convey a definitive message: although technology and urban design are significant, the primary emphasis for effective crime prevention is in education, preventive measures, and the strategic integration of digital tools.