ARTIFICIAL INTELLIGENCE FOR CRIME PREDICTION AND PREVENTION – A LITERATURE REVIEW

Abstract

Crime prevention is a key concern in modern society, with significant implications for public safety and informed law enforcement decision-making. An innovative approach in this direction is the use of Artificial Intelligence (AI) to analyze statistical data on crime history. This paper explores the current state of the art of using AI in crime assessment and prevention, presenting current methods, and techniques, such as Machine Learning and Deep Learning, which are applied to identify crime patterns and trends. Throughout the analysis, the advantages, and challenges of using AI in this context are discussed and relevant case studies are highlighted where AI has had a significant impact in reducing crime. Finally, it outlines emerging research directions, including improving crime prediction algorithms and applications integrating data from various sources and developing robust mechanisms for evaluating the performance of AI models. By exploring these issues, the paper provides a broad perspective on the current state and future directions for crime prevention using Artificial Intelligence.