The 5G Use Cases Lab at International Institute of Information Technology Hyderabad is a next-generation innovation hub established under the Government of India’s “100 5G Use Cases Labs Initiative.” The lab empowers students, researchers, startups, and industry partners to explore real-world 5G applications in areas such as smart cities, IoT, Edge Computing, smart surveillance, AI, and AR/VR, through advanced 5G infrastructure and collaborative research opportunities.

Crowd Monitoring Using 5G Technology

Crowd Monitoring System leverages advanced 5G communication technology, AI-powered video analytics, and a centralized monitoring dashboard to enable real-time public safety and crowd intelligence management. The system is designed to support smart cities, public events, transportation hubs, campuses, industrial zones, and other high-density environments where continuous monitoring and rapid response are critical. The architecture consists of three major components:

  • 5G Smart Cameras
  • 5G NMS (Network Management System) Server
  • Centralized Monitoring Dashboard
BYPL(Giz) and IIIT-H Collaboration

Features

Real-Time People Counting

The system continuously detects and counts the number of individuals present in a monitored area. This enables authorities to monitor occupancy levels, regulate crowd movement, and ensure safety compliance.

Crowd Density Analysis

AI algorithms analyze spatial distribution and crowd concentration levels in real time. High-density zones can be automatically highlighted to prevent overcrowding and potential hazards.

Fall Detection

The system detects incidents where a person collapses or falls unexpectedly. Immediate alerts can be generated for emergency response teams, improving safety in public and healthcare-related environments.

Fight Detection

Using behavioral analysis and motion tracking, the system identifies aggressive interactions and physical altercations. Security personnel can be instantly notified for quick intervention.

Loitering Detection

The solution detects individuals or groups remaining in restricted or sensitive areas for extended durations. This helps improve security and prevent suspicious activities.

Running Detection

Sudden running activity in public spaces may indicate emergencies or panic situations. The system identifies abnormal running patterns and triggers alerts for further investigation.

Emotion Recognition

The AI analytics engine can classify facial emotions into categories such as:

  • Happy
  • Sad
  • Angry
  • Neutral