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@article{200440,
        author = {Kumar Rai Chandna and Dr Premal Patel},
        title = {A Comprehensive Analysis of Hotspot Policing as a Crime Reduction Strategy with a Focus on Geographic Crime Patterns, Predictive Techniques, and Targeted Police Interventions},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {1931-1936},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200440},
        abstract = {This research presents a data-driven approach to hotspot policing for crime reduction by developing a dynamic and automated patrolling system based on geographic location and time. The study uses clustering techniques to analyze historical crime data and identify high-risk areas by grouping incidents according to spatial and temporal patterns, enabling the generation of optimized patrolling routes for police deployment. The proposed system continuously updates these routes using new incoming crime data, making the patrolling process adaptive and responsive to changing crime patterns. By integrating geographic mapping and predictive analysis, the framework improves resource utilization, reduces response time, and enhances the overall effectiveness of law enforcement strategies. This approach supports proactive policing and contributes to smarter urban safety management. The research aligns with the goals of the United Nations Sustainable Development Goals, particularly SDG 11 (Sustainable Cities and Communities) and SDG 16 (Peace, Justice, and Strong Institutions), by promoting safer communities, efficient policing systems, and the use of innovative technology for public safety.},
        keywords = {Hotspot Policing, Crime Reduction, Geographic Clustering, Predictive Policing, Patrolling Route Optimization.},
        month = {May},
        }