Russian AI System Tackles Public Transit Overcrowding in Real Time

A neural network developed by NtechLab is helping city officials in Nizhny Novgorod manage overloaded bus stops by analyzing crowd density live.

To address the chronic problem of overloaded public transportation, Russia is deploying AI in a highly targeted way. A neural network developed by the IT company NtechLab has been trained to monitor crowd levels at bus stops in real time, flagging overcrowded zones and sending alerts to city dispatchers. In response, more vehicles can be rerouted to underserved areas.

The pilot program is now underway in Nizhny Novgorod, where the technology will be tested at 300 bus stops across the city.

Nizhny Novgorod has become a national leader in urban AI deployment. Beyond transit, neural networks are being implemented in housing, construction, and healthcare. For example, NtechLab’s systems are already used to monitor waste collection points and optimize municipal services.