Our system counts people at transit stops, sends timely crowding alerts, and helps dispatchers deploy more vehicles to routes when needed.

300+ stops

now covered by our video analytics

Using AI to reduce crowding and shorten wait times at public transit stops

Nizhny Novgorod

Visualize passenger crowds at stops in real time

Reduce overcrowding and shorten wait times during peak hours

Quickly adjust and reinforce routes

Client challenge

We integrated our AI with the city's existing video surveillance system. We set up automated alerts for the dispatch center.

Cameras at transit stops transmit the video stream to the analytics system.

1.

The system sends the dispatcher a notification with the address, time, and associated route.

3.

The dispatcher deploys more vehicles or adjusts schedules accordingly.

4.

Cameras at transit stops transmit the video stream to the analytics system.

2.

Crowd forms at stop during rush hour

The system alerts the dispatcher who deploys additional vehicles

Demand drops as more vehicles were deployed

AI shows the reduction at specific locations, and the dispatcher pulls back the extra vehicles

Need to prepare next day's schedule

Reports on daily/weekly peaks allow adjusting the schedule proactively

We can deploy a pilot program using your existing infrastructure and demonstrate initial results within weeks.

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