Suraksha: Spatio-Temporal Crime Forecasting and Micro-Location Analysis

Jayawardana, Hiranya and Pathmaperuma, Madushi Hasara (2024) Suraksha: Spatio-Temporal Crime Forecasting and Micro-Location Analysis. Journal of Electrical Systems (JES), 20 (9). pp. 1635-1641. ISSN 1112-5209

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Official URL: https://journal.esrgroups.org/jes/article/view/467...

Abstract

Suraksha, a spatiotemporal crime prediction system, designed to elevate crime prevention with precise insights, empowering law enforcement for a safer tomorrow. Utilizing vast datasets, machine learning, and GIS, it forecasts crime hotspots by incorporating Chicago's extensive crime statistics. Addressing both precision and ethical considerations, Suraksha achieves RMSE values of 0.0874 (latitude) and 0.0602 (longitude), marking a leap in predictive policing. This pioneering approach aims to transform public safety by proactively combating crime, ensuring community well-being through innovative data-driven strategies.


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