Linker Vision ← All products / Metro

Metro

Metro Safety

Metro Guardian AI transforms existing metro CCTV infrastructure into a 24/7 AI-powered sensing and operational decision-support system using AI Video Analytics, Vision Language Models (VLM), and Digital Twin / Physical AI technologies. The platform continuously analyzes video across stations, platforms, tracks, entrances, and other critical areas to detect crowd congestion, restricted-area intrusion, unattended objects, unsafe behavior, flooding, construction-zone anomalies, and fire and smoke detection. Without requiring large-scale replacement of existing CCTV infrastructure, Metro Guardian AI upgrades traditional passive surveillance into a proactive AI system that detects events, generates real-time alerts, and helps operators respond faster and more effectively.

VLM output

A handful of masked passengers stand in an orderly line along the platform screen doors of an underground metro platform, most looking at phones while waiting for a train. Over the four frames the group shifts slightly and one more person joins the queue; a train is visible stationary behind the closed platform doors and no incident occurs.

  • Platform Edge Line CrossedNo
  • Passenger Fall Or IntrusionNo
  • Crowd DensityLow
  • Waiting Passengers Count8
  • Queue OrderlyYes
  • Screen Doors ClosedYes
  • Train At PlatformYes
  • Face Mask UsageMost
  • Staff PresentNo

Customer challenges

1

Thousands of CCTV streams make continuous manual monitoring impractical

2

Safety and operational incidents often depend on manual observation, patrols, or passenger reports

3

Track intrusion, unattended objects, and unsafe behavior require immediate attention

4

Crowd congestion and queue conditions are difficult to monitor consistently across stations

5

Flooding and environmental conditions can disrupt station and network operations, as well as passenger safety.

6

CCTV, VMS, alarms, and operational information are often managed across separate systems

7

Traditional video analytics are typically built for individual use cases, making new scenarios costly and time-consuming to deploy

8

Transit agencies need to modernize operations while maximizing existing CCTV investments

Customer benefits

Establish 24/7 proactive AI monitoring across metro environments

Shift from manually watching CCTV to AI-assisted monitoring

Detect potential safety and operational issues earlier

Shorten Detection → Verification → Response time

Reduce control-center workload associated with continuous CCTV monitoring

Transform existing cameras into intelligent operational sensors

Rapidly introduce new use cases through VLM-based analytics

Scale from a single station to multiple lines and network-wide deployments

Key features

AI Passenger & Crowd Intelligence

Monitors crowd density, platform and concourse congestion, queues and abnormal crowd formation, with real-time peak-hour alerts.

AI Safety & Security Detection

Detects track and restricted-area intrusion, unattended objects, unsafe or abnormal behavior, falls and person-down events, and monitors construction and restricted zones.

AI Infrastructure & Environment Monitoring

Detects flooding, fire and smoke, camera obstruction, blur and health issues, and other infrastructure and environmental anomalies through 24/7 AI inspection of critical areas.

VLM-Powered Event Detection

Defines detection scenarios in natural language for complex event and scene understanding, enabling rapid deployment of new AI use cases with flexible rules per station and environment.

Smart Incident Management

Delivers real-time alerts with automatic event video capture and evidence retention, AI event classification, centralized camera, station and event management, an AI-assisted alert plus human verification workflow, and integration with existing VMS and control-center systems.

Before & after

Before Operators manually monitor CCTV After — with Linker AI Nexa AI continuously monitors and identifies relevant events
Before Incidents depend on manual or passenger reporting After — with Linker AI Nexa AI proactively detects and alerts operators
Before Video is primarily reviewed after an incident After — with Linker AI Nexa Relevant video evidence is surfaced in real time
Before Crowd conditions rely on visual observation After — with Linker AI Nexa AI continuously monitors crowd and queue conditions
Before Safety risks may be discovered after escalation After — with Linker AI Nexa AI identifies potential risks earlier
Before CCTV primarily serves as a surveillance system After — with Linker AI Nexa CCTV becomes a real-time operational sensing network
Before Individual AI models for individual scenarios After — with Linker AI Nexa VLM enables faster expansion of new use cases
Before Information is fragmented across systems After — with Linker AI Nexa AI events are centrally managed
Before Reactive operations After — with Linker AI Nexa Proactive, AI-assisted operations