Development and Implementation of Face Recognition Technology for Criminal Identification and Public Safety

M.Vishnu Vardhana Roa; K. Lohitha; J. Akhila; K. Sathwika

doi:10.62127/aijmr.2026.v04i02.1275

Development and Implementation of Face Recognition Technology for Criminal Identification and Public Safety

Author(s)	Dr. M.Vishnu Vardhana Roa, K. Lohitha, J. Akhila, K. Sathwika
Country	India
Abstract	Criminal identification in rapidly growing urban environments continues to rely heavily on traditional methods such as manual CCTV monitoring, eyewitness testimonies, and time-consuming verification processes, which often lead to delays, inaccuracies, and reduced situational awareness. These limitations have become more evident with increasing urbanization, population density, and the growing sophistication of criminal behavior. The core problem stems from fragmented criminal databases, lack of real-time coordination among agencies, and minimal public participation in reporting mechanisms, creating a substantial gap in proactive crime prevention. To overcome these challenges, this research develops CrimeVision, an AI-powered facial recognition and public safety platform designed to transform static surveillance into an intelligent, automated, and community-inclusive safety system. The proposed system integrates DeepFace with ArcFace facial embeddings, multi-backend detectors such as RetinaFace and MTCNN, and OpenCV preprocessing to ensure high-accuracy face matching from both uploaded images and live camera feeds. Additionally, the system incorporates GPS-based geolocation, interactive map visualization, role-based dashboards, OTP-secured authentication, multilingual interfaces, and real-time alert mechanisms for efficient monitoring. Public users can report suspicious activities with images and location details, while police personnel can manage criminal records, validate reports, track incidents on a map, and receive instant detection alerts. By combining AI-driven recognition, geospatial intelligence, and public engagement within a secure and scalable web architecture, CrimeVision significantly enhances identification speed, reduces manual investigation workload, strengthens community–police collaboration, and supports timely law enforcement response. Ultimately, this system offers a cost-effective, accessible, and technologically advanced framework for improving public safety and enabling smarter, data-driven urban policing.
Keywords	Facial Recognition, Crime Detection, Deep Learning, Computer Vision, Public Safety
Discipline	Engineering
Published In	Volume 4, Issue 2, March-April 2026
Published On	2026-04-06
DOI	https://doi.org/10.62127/aijmr.2026.v04i02.1275

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Development and Implementation of Face Recognition Technology for Criminal Identification and Public Safety

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