AI Makes City Management More Efficient in Dubna
Artificial intelligence systems are being introduced into the urban management of the Russian science city of Dubna. It is already clear that these technologies allow city services to respond to problems faster and resolve them more effectively.
AI in Urban Governance
The Regional Management Center in the science city of Dubna has begun actively integrating artificial intelligence systems into its operations to improve the effectiveness of city management. AI is used for the automated analysis of video streams from surveillance cameras. Algorithms detect faulty street lighting, accumulations of garbage, and other types of urban violations. The system processes large volumes of data from multiple sources – video cameras, social media, and the Dobrodel public feedback portal – and promptly alerts the relevant municipal services.
AI tools also help analyze statistics related to residents’ requests, compare indicators across current and previous periods, and generate forecasts. In the near term, the city plans to train municipal specialists to work directly with these technologies.
For Russia’s IT sector, this project serves as a clear example of the practical application of AI in managing urban processes. It aligns with smart city trends and with the federal-level development of the “safe city” concept. AI modules in video surveillance go beyond basic video processing. They deliver automated big data analytics that significantly increase management responsiveness. As a result, authorities react more quickly to urban issues. Time spent on routine tasks is reduced, while forecasts of how situations may develop become more accurate.
Such gains in the efficiency of digital regional governance are an integral part of the global shift toward smart cities, where AI analytics play a central role in public safety, infrastructure management, and improving quality of life for residents.
Integration Outlook
At this stage, direct export of the Dubna solution is unlikely, since it is embedded within municipal services. Even so, AI-based automated camera analysis could attract interest from other Russian regions as well as from Kazakhstan, Belarus, and Serbia – countries that are also investing in smart city development.
Within Russia, the prospects are more immediate and tangible. One priority is integration with regional platforms, including a unified video surveillance platform overseen by the Ministry of Digital Development, which is designed to process AI video streams from all regions. Further expansion of AI capabilities also appears likely. This includes recognizing high-risk situations, automatically classifying incidents, and preventing negative scenarios before they unfold. At the same time, the qualifications of regional specialists are expected to rise, alongside continued development of digital infrastructure.
As these systems evolve, policymakers and developers must pay close attention to regulation of AI in public spaces. This includes rules for processing citizens’ video data, ensuring the quality of datasets and algorithms, and maintaining strong cybersecurity protections for large-scale video analytics.
Nationwide Deployment
The development of automated video surveillance systems is an active trend across Russia. In 2025–2026, around 2 billion rubles (approximately $24 million) were allocated to create a unified federal service for AI-based processing of video data from regional security cameras.
In 2025, the Sverdlovsk region deployed smart cameras with AI to manage traffic and analyze transportation flows, demonstrating that similar technologies can be implemented at the regional level. Russian researchers have also developed a neural network capable of detecting street violence based on video footage, illustrating how AI applications in public safety are moving toward more complex analytical tasks. These examples have made it increasingly clear that such digital technologies represent a long-term trajectory for urban development.
Dubna has become one of the cities where AI is being applied as a tool to improve the quality of municipal governance. This reinforces the broader trend toward digitalization of city services across Russia.
Over the next two to three years, AI analytics are expected to scale across Russian regions. The likely evolution will move from simple alerts, such as garbage collection issues or lighting failures, toward more complex predictive analytics and automated service notifications. Greater regulatory attention to AI in public services – including data protection, facial recognition ethics, and video data processing – will become a critical element of how these systems mature.
