Neural Networks on Duty: Yamal Boosts Public Safety With AI-Powered Smart Cameras
In the Yamalo-Nenets Autonomous Okrug, video surveillance has evolved from a tool for recording incidents into an intelligent network capable of preventing and solving crimes.
Recognizing One Person Among Thousands
Since 2020, the unified video surveillance system has expanded ninefold, reaching 6,500 cameras, with 2,000 of them equipped with artificial intelligence algorithms. Crime detection rates in public spaces have reached 91%, while the overall number of incidents has fallen by 18% over two years. In 2024 alone, AI analytics helped locate 789 missing persons and suspects. In 2025, that figure increased by 1.5 times.
The key advantage of the new system lies in its shift from passive observation to active analysis. AI-enabled cameras do more than record video – they identify events, objects and suspicious situations in real time, including abandoned items, fights and person searches based on physical descriptions. This allows police to respond immediately, often before an offense is committed. The preventive effect has become as significant as the rise in crime detection. Plans for 2026 include expanding the network under the “My Courtyard” program and at city entry points, extending safety beyond central streets to residential neighborhoods.
Finding Both People and Vehicles
In many cities, smart cameras not only document offenses but also help prevent them. AI-based systems are becoming a standard tool for public safety and urban space management. In St. Petersburg, cameras automatically flag potentially dangerous actions near cultural heritage sites. In Khakassia, AI-powered cameras assist in locating stolen vehicles and identifying suspicious cars seen near crime scenes. Kabardino-Balkaria uses similar video systems to search for missing persons and criminal suspects.
It is therefore logical that the Yamalo-Nenets Autonomous Okrug will soon introduce a unified control dashboard for law enforcement, automated alerts for police, emergency services and ambulances, and deeper integration of video surveillance with smart city components. The successful Yamal case could serve as the basis for a ready-made AI video analytics platform for other Russian regions and potentially for CIS markets. The technology has proven its effectiveness, demonstrating reliability and adaptability.
Security as a Service
Yamal’s example shows that investments in intelligent security systems pay off not only in statistics but in the most important outcome – a stronger sense of safety among residents. The system is already moving toward predictive analytics, where algorithms analyze behavioral patterns and identify risks before they materialize.
AI technologies have become a practical tool for improving quality of life even in remote regions. The next step is turning this experience into a scalable digital product that can enhance safety across Russia and beyond.
