A Quantitative Study on Real-Time Police Patrol Route Optimization using Dynamic Hotspot Allocation

Abstract: A quantitative study on the optimization of police patrol routes in real-time using dynamic hotspot allocation is presented in this article. Ensuring public safety necessitates addressing the difficulties law enforcement agencies encounter in optimizing patrol routes within limited resources. In dynamic environments, static patrol route planning and traditional random routing are inadequate. In order to prevent crime, this study suggests using big data analysis to pinpoint crime hotspots and create patrol routes that are most effective. Our suggested approach, when paired with the Random Forest algorithm, predicts crime-prone areas by combining 911 incident response data and crime datasets. This allows for the efficient use of police resources and successful preventive measures. A greedy algorithm is used to steer patrol units toward the best routes, maximizing their presence close to hotspots. Besides, a Hamilton way is powerfully made based on overhauled hotspots and crisis call hubs. Whereas the spatial selection technique addresses restrictions of randomized investigation, productive policing remains pivotal for societal well-being and financial development. Progressions in innovation enable decision-makers with real-time data on criminal exercises, guaranteeing resource-friendly strategies inside budgetary imperatives. Successful communication with the public is crucial, as security impacts different perspectives of society, including venture choices. Hence, cutting-edge approaches are crucial for informed decision-making and keeping up with general security.

Rakesh Ramakrishnan, Soumithri Chilakamarri, Roopalatha Mangalseth Budda and Ashik Dawood Mohammed Anifa. “A Quantitative Study on Real-Time Police Patrol Route Optimization using Dynamic Hotspot Allocation”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.6 (2024). http://dx.doi.org/10.14569/IJACSA.2024.0150603

@article{Ramakrishnan2024,
title = {A Quantitative Study on Real-Time Police Patrol Route Optimization using Dynamic Hotspot Allocation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150603},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150603},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {6},
author = {Rakesh Ramakrishnan and Soumithri Chilakamarri and Roopalatha Mangalseth Budda and Ashik Dawood Mohammed Anifa}
}