Spatio-temporal crime maps and their role in crime reduction In light of artificial intelligence technologies
DOI:
https://doi.org/10.59759/law.v5i2.1803Keywords:
Spatio-temporal Crime Mapping, Crime Prediction, Artificial Intelligence, Crime Geography, Algorithmic CriminologyAbstract
Developing effective crime prevention strategies depends on understanding the geographic realities of crime events and then predicting their number, location, and timing. In this regard, recent studies in the field of criminology research focus on the spatial and spatiotemporal analysis of criminal activities. Studies reveal that criminal activities exhibit similar spatial patterns with varying temporal patterns. Therefore, the development of predictive models for criminal activities can directly support crime prevention and proactive deterrence planning. By analyzing the role of spatiotemporal crime maps in reducing crime in light of artificial intelligence through a critical descriptive approach, which includes analyzing and extrapolating the research literature on artificial intelligence and spatiotemporal crime patterns, The current research concludes that spatio-temporal mapping allows for the prediction of crimes and methods of committing them, as well as the times and places where the risk of crime is highest. Artificial intelligence also provides an opportunity for proactive interventions to deter crime or reduce the chances of it occurring. Furthermore, spatio-temporal crime patterns are linked to specific factors, and analyzing them provides multiple pieces of information to predict what may happen in the future.
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