AI-based technologies in transportation for the Moscow Region

Detection of railway track crossing violators

In 2022, the Urbantech Group served as the technology partner in a project focused on monitoring and enforcing railway crossing regulations through the deployment of facial recognition cameras. The initiative, led by the Moscow Region’s Ministry of Transport and the Ministry of Internal Affairs’ Transport Department for the Central Federal District, aims to reduce railway-related fatalities.

Since the project’s inception in the Moscow Region, more than 2,000 individuals have been subjected to administrative penalties, and the number of casualties at railway stations equipped with this surveillance system has been reduced by 90%.

Analysis of queues at public transport stops

In 2022, in order to proactively detect operational disruptions in passenger transport and swiftly addressing issues through collaboration with transit providers, the Urbantech Group developed and deployed an analysis module to monitor queues at bus stops in the Moscow Region.

The module’s neural network processes video feed from cameras located at the stops to detect the number of people and compiles reports on peak congestion times. Based on these insights, the operator can make decisions to dispatch additional vehicles to the route as needed.

In the testing phase, the system demonstrated a recognition accuracy of 90%. The system is currently connected to 25 cameras. To date, the highest recorded queue observed by the system at any stop was 44 people.

Taxi Control system

Since 2021, an automated compliance monitoring system has been in use in the Moscow Region to ensure that taxi vehicles adhere to the regionally approved color scheme standards.

The system operates on a neural network that assesses footage from the regional traffic enforcement cameras, identifying taxis that violate the color scheme regulations. The data regarding these violations is forwarded to the Moscow Region Ministry of Transport for additional verification. Subsequent to verification, taxi companies receive official notifications to correct these violations.

During its operation, the system has identified over 30,000 taxi vehicles in the Moscow Region that were not in compliance with the proper color scheme.