Case Study

Home >AI-Powered Prison Tracking and Monitoring System

AI-Powered Prison Tracking and Monitoring System

We developed a custom AI Camera-Based Tracking and Attendance System specifically designed for correctional environments. Using facial recognition, intelligent rule enforcement, and real-time alerting, the system streamlines monitoring while enhancing safety and accountability.

Prisoner tracking inside prison

Prison inside or not

Unknown person alert inside cell

Prison guard tracking

Realtime alerts on Prison CMS

Live monitoring and recording to monitor using IP cameras

Client Overview

Client

A high-security prison facility focused on modernizing operations

Use Case

Automated tracking and attendance of individuals using AI-powered facial recognition

Location

India

End Users

Prisoners, Guards, Control Room Operators, Administrative Staff

Problem Statement

Conventional monitoring methods within the facility were facing critical challenges:
  • Manual headcounts were time-consuming and repetitiv‘
  • Human errors led to potential security riskœ
  • No real-time visibility into zone-based movemen
  • Dependency on paper-based logs and physical supervision
To address these inefficiencies, the facility required a secure, automated, and real-time system to monitor and track movement and presence accurately within restricted zones.

System Workflow

Initial Configuration

  • Person Types: Define roles like Prisoner, Guard, Visitor
  • Rules: Set rules for zone access (e.g., cell blocks, yard, kitchen) and time-based shifts
  • Devices: Register and assign AI-enabled cameras to monitor critical areas

AI Server Setup

  • Configure the AI Server with details such as CPU, RAM, OS, MAC address, and IP
  • Enable seamless camera communication via MQTT protocol

Person Enrollment

  • Required details include:
  • Name, Age, Gender
  • Unique Person Number
  • Face Photograph
  • Assigned Access Rules and Devices
  • Person Type (e.g., Prisoner, Guard, Visitor)

Live Tracking & Attendance

  • AI cameras scan and identify faces at zone checkpoints
  • The system validates presence and triggers alerts for:
  • Recognized Individuals
  • Unknown Faces
  • Obstructed or Unclear Faces
  • Absence within required zones or shifts

Real-Time Monitoring

  • Web-based dashboard accessible by authorized personnel
  • Logs with timestamps for all movement and alerts
  • Daily, weekly, and zone-specific attendance reports

Tech Stack Overview

Frontend

React.js (Admin Control Panel)

Backend

Node.js with Express.js

Database

MongoDB

AI Engine

Python-based face recognition

Camera Communication

MQTT (Camera AI Server)

Deployment

On-premise within a secure, isolated network environment

Core Features Delivered

  • Real-time AI-driven facial recognition
  • Seamless integration with on-site AI camera infrastructure
  • Zone-based rule configuration and enforcement
  • Digitized attendance and movement logs
  • Secure, role-based user access for staff and operators
  • Automatic alerts for unauthorized access and anomalies
  • Comprehensive reporting for compliance and review

Deployed Across Multiple Locations

This AI-powered tracking system has been successfully deployed and adapted for various secure environments, including:
  • High-security correctional facilities
  • Industrial campuses requiring restricted area monitoring
  • Secure government and defense-controlled compounds
  • Large factories with sensitive zones
  • Research labs and infrastructure zones with access control needs
  • Juvenile and rehabilitation centers
  • Private institutions focused on automated personnel tracking
The platform’s modular structure allows easy replication and adaptation across various types of correctional environments.

Impact & Results

  • Over 90% reduction in time spent on manual attendance and monitoring
  • Fully digitized and tamper-proof record keeping
  • Significantly enhanced facility security through automated alerting
  • Improved real-time monitoring and response readiness
  • Reduced reliance on manual supervision for routine checks