A Neural Network Will Eliminate Fuel-Station Lines in Russia

Smarter Traffic Flow for Fuel Stations

Russian developers have created an AI system designed to prevent long queues at fuel stations. Built by NtechLab, a technology partner of Rostec, the neural network analyzes video feeds from cameras and automatically alerts station personnel when congestion begins to form, allowing staff to react instantly.

The technology continuously monitors vehicle activity across the station’s territory. Artificial intelligence detects clustering of cars and immediately notifies the station manager, enabling staff to redirect drivers to open pumps or activate additional fueling points. If on-site personnel do not respond, the alert is automatically forwarded to the network’s central office.

One of the unique advantages of the solution is its adaptability and seamless integration into existing infrastructure. It requires no complex installation and can be deployed at fuel stations of any size.

Saving Drivers’ Time—and Their Patience

The system is a clear example of how computer vision technology can solve real, practical problems. In this case, the neural network helps drivers save time and reduces frustration by eliminating unnecessary waiting.

NtechLab is already known for its transportation innovations. Its neural networks help locate stolen vehicles, detect road-surface damage, and even optimize public-transport routes by analyzing passenger flow. Integrating AI for queue management at fuel stations is a logical next step toward building an intelligent ecosystem for urban mobility and road infrastructure.