Solution · Transportation
Passenger Flow - counts, queues, peaks.
Know volume by period. Plan the peak, not the guess.
Station and airport ops teams who need counts and queues for peak planning.
The challenge
More cameras. Same blind spots.
Stations and trains already record everything - crowding, loitering and risk still depend on someone staring at the wall.
- 01
Nobody can watch every screen
Peak hour multiplies views; important moments drown in ordinary motion.
- 02
Crowds are guessed, not measured
Queue and flow decisions wait on complaints or hand counts - too late for the rush.
- 03
Finding an incident takes hours
After a report, teams scrub video across stations and onboard cameras.
- 04
Old and new cameras do not connect
Partners need stable feeds; the estate is a mix that breaks integrations.
Sound familiar?
By the numbers
Stations record everything. Operators cannot watch everything.
Transit security needs models and search - not a taller camera wall.
~90%
of CCTV video goes unwatched without AI / triage workflows
*1
Peak pressure
queues and crowds are still guessed until complaints spike
*2
Hours
to scrub multi-station footage after an incident report
*3
- *1 Industry CCTV utilization analyses (security operations research) - the large majority of recorded video is never reviewed.
- *2 Common transit-ops gap - passenger flow decisions lag without counting / queue analytics.
- *3 Typical investigation cost on multi-camera estates without unified VMS search and tracking.
How we solve it
AI alerts plus a VMS you can search.
Models for crowds and risk, searchable video, and stable feeds for mixed camera estates.
- 1
Alerts on what matters
Counting, loitering, crowds, tampering and more - each as its own AI module.
- 2
Crowd and queue insight
Passenger counts and queues for planning - not only after the rush.
- 3
Find footage fast
Live, playback and filters across station and onboard cameras.
- 4
Feeds that stay stable
Mixed camera estates publish clean stream endpoints for partners and tools.
This is the simpler path.
ROI conversation
From camera wall to actionable events.
ROI shows up as operator time and faster find-back - not more screens.
4×
operator leverage target
Model events surface crowding, loitering and cabin risk instead of staring at every tile.
Faster
incident find-back
Searchable VMS across station and onboard cameras.
Clearer
peak planning
Counting and queue analytics for rushes - not only after-action review.
4× leverage is a planning target for AI-assisted monitoring vs pure manual camera walls; camera density and model mix affect results.
How it works
From station survey to live models
- 01
Map cameras & risks
Platforms, concourses, forecourts, cabins - which models matter first.
- 02
Stand up VMS + proxy
Unified video and stable stream endpoints.
- 03
Enable AI modules
Turn on the models you need; leave the rest off until ready.
- 04
Train operators
Search, review and export in the tools the shift already uses.
Ready to map step one?
What's in the package
Transit security as a clear offer.
AI modules and platform features - listed so procurement and operations review the same scope.
- Passenger counting by period and zone
- Queue and crowd pressure analytics
- Optional category breakdowns
- Hooks for passenger-information messages
- Dashboards for ops and planning
After go-live
What teams notice first
Peak plans from real counts
Queue pressure before complaints
Shared numbers for ops and commercial
Want outcomes like these on your site?
Sentrinel AI modules
AI models in this package
Each model is its own module - browse the grid or open Technology for detail.
Secure the station without another camera wall.
Share your camera count and priority risks. We will map which AI modules and VMS scope fit.
FAQ
Station & transit security - FAQ.
OCC and security leads comparing AI assist vs more camera tiles.
Do operators still watch live video?
Yes - AI surfaces crowding, loitering, cabin and platform risk so humans decide. It is leverage, not a dark OCC.
Which models ship in the package?
Transit-relevant modules (crowd/queue, loitering, passenger behaviour, and related) are selected per station class in discovery.
Works with our existing VMS?
Often yes via RTSP/ONVIF. Some operators unify on VVMS; others keep the NVR and add Sentrinel AI + proxy.
Privacy and recording policy?
Retention and redaction policy stay under your security / legal rules. We configure storage classes - we do not invent policy for you.
Pilot one station first?
Recommended. Prove alert quality and OCC workflow on one site before a corridor roll-out.
Tell us the problem — we'll shape the solution.
A short discussion. No pitch theater. We listen, then compose a clear path.