Computer Science
India
April 10, 2026
Suraksha Setu: AI-Driven Criminal Identification Using Facial Recognition Technology with Aadhaar Integration for Scalable Intelligent Public Safety in Urban India
Suraksha Setu is an AI-powered dual-platform public safety ecosystem designed to address the critical operational gaps in
Indian law enforcement. The system integrates Facial Recognition Technology (FRT) using the DeepFace framework (VGGFace2 backbone), real-time multi-class object detection via YOLOv8 fine-tuned on a 14,200-image custom dataset, and
biometric identity verification through the UIDAI Aadhaar Authentication API 2.5. The architecture comprises two primary
subsystems: (1) a Citizen Safety Portal providing geofence-triggered crime alerts via Firebase Cloud Messaging, SOS GPS
triangulation, and a community gamification layer; and (2) a Police Operational Dashboard delivering live AI-monitored CCTV
analytics, LIDAR/UGS-based restricted-zone intrusion detection, crime heatmap visualization via MongoDB GeoJSON, and
centralized Aadhaar-linked offender database access.
Comprehensive evaluation demonstrates that DeepFace achieves 94.8% facial recognition accuracy under operational CCTV
conditions, surpassing FaceNet (91.7%) and ArcFace (89.3%). YOLOv8 attains a mean Average Precision (mAP@0.5) of
91.3% across five threat categories, with weapon detection reaching 92.1% F1-score. System response latency averages 1.2
seconds for SOS dispatch and 2.8 seconds for FRT matching — a 75–80% reduction over conventional systems. An ablation
study confirms that each architectural component contributes measurably to system performance. A security assessment across
seven threat vectors demonstrates compliance with NIST SP 800-175B, UIDAI regulations, and OWASP Top-10 standards.
Suraksha Setu represents a replicable, nationally scalable framework for AI-integrated, constitutionally compliant smart
policing
By Sachin Chaurasiya · Vishwaniketan iMEET