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Title	Predictive Policing In Urban Environments Using Random Forest Framework For Safer Smart Cities
ID_Doc	42895
Authors	Jain R.; Chilambuchelvan A.; Kumar M.S.; Ambigaipriya S.; Rafeeq M.D.; Sengottaiyan K.
Year	2024
Published	2024 15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024
DOI	http://dx.doi.org/10.1109/ICCCNT61001.2024.10723873
Abstract	Rising crime rates are smart cities, needs the utilization of new methods to improve safety. A predictive policing framework is proposed addresses the urban area crime in this research using a Random Forest algorithm. The policy enforcement issue to distribute resources for preventing and addressing criminal activities is hence studied. Precise models are required for urban environments that face challenges. Random Forest analyzes the environmental factors, socio-economic indicators and past crime data. Predictive Random Forest identifies crime hotspots patterns. The precision, recall, and F1 score assess the model and it finds the efficacy of the proposed method in forecasting crime incidents enabling policy to enhance public safety in urban areas. © 2024 IEEE.
Author Keywords	Crime Prevention; Predictive Policing; Random Forest; Smart Cities; Urban Environments

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