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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62126
Volume:
10 |
4 |
April 2026
Pages:
1-11
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
BE
Angel college of engineering and technology
BE
Angel college of engineering and technology
BE
Angel college of engineering and technology
BE
Angel college of engineering and technology
BE
Angel college of engineering and technology
Public crime reporting remains inefficient due to limited accessibility and slow response mechanisms. This paper presents an Online Crime Reporting System — a Flutter-based web application with a FastAPI backend — that allows citizens to submit geo-tagged crime reports with location, category, description, and image evidence. The system integrates an AI-driven spatial analysis layer using Kernel Density Estimation for risk mapping, DBSCAN clustering for hotspot detection, and a predictive model for forecasting future crime activity. Results are visualized on an interactive map with real-time heatmaps, danger zones, and crime markers. Role-based access separates citizen and admin workflows, with JWT-secured endpoints throughout. The system provides a practical, accessible tool for community-driven crime intelligence to support law enforcement decision-making.
KEYWORDS
This paper presented an Online Crime Reporting System that addresses the limitations of existing reporting mechanisms by combining a Flutter-based mobile application with a FastAPI backend and an AI-driven spatial intelligence engine. Citizens can submit geo-tagged crime reports directly from their smartphones, while administrators verify and monitor crime patterns through an interactive map rendering KDE risk surfaces, DBSCAN hotspots, danger zones, and future risk predictions in real time. Results confirmed that the system produces meaningful spatial outputs and delivers a practical, accessible platform that bridges citizen participation and intelligent crime analysis to support proactive law enforcement
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Publication Date
4/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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