Ulan-Ude Declares War on Illegal Dumping with AI-Powered Smart Surveillance

In Russia’s Republic of Buryatia, a new AI-based surveillance system is being deployed to combat the growing crisis of unauthorized waste dumps. This digital initiative marks the beginning of a smarter future for public infrastructure management.

Technology on the Front Lines

Ulan-Ude is taking a high-tech approach to a very real problem: illegal dumping. The city is piloting a smart surveillance system that uses artificial intelligence to automatically detect violations at waste collection points. Cameras mounted on container sites feed real-time video to AI algorithms that monitor for off-container littering, the formation of new illegal dumps, and subtle landscape changes that indicate waste accumulation. A centralized platform aggregates footage from 1,000 monitored locations, eliminating the need for manual video review.

A Mounting Sanitation Crisis

Buryatia is facing a serious waste management problem. In June 2025, a court-ordered cleanup removed 200 cubic meters of construction and household waste from Pecherskaya Street alone. Community cleanup campaigns like 'Clean Thursday,' which mobilized 500 volunteers to eliminate 25 dumps and remove 280 cubic meters of waste, have helped—but not solved—the issue. The limitations of manual monitoring have made new technologies not just helpful, but necessary.

AI Expands Across the Regions

If the Ulan-Ude pilot proves successful, it could become a model for other cities. The project draws on proven solutions, including the Moscow Region’s AI-based system that has already shown impressive results. Beyond surveillance, the system could integrate with GIS platforms for mapping dump locations and optimizing garbage truck routes. AI-generated fines linked to vehicle license plates could address littering from cars.

There are currently over 15,000 illegal dumps registered across Russia—and that’s only the ones we know about. New sites are being discovered every year, but no one can say exactly how many exist. AI will help us identify all of them. Once the model achieves consistent accuracy, we can shift from pilot projects to continuous monitoring, enabling rapid response to environmental violations

Alexander Vedyakhin

First Deputy Chairman of the Executive Board, Sberbank

The system can also send automatic alerts to environmental prosecutors, and Big Data analytics can identify 'hotspots' before problems escalate. This fusion of AI and smart infrastructure could enable a new standard for ecological monitoring.

From Cleanup Crews to Code

Moscow Region was the first in Russia to apply AI to tackle illegal dumping. A few years ago, UrbanTech developed a neural network for the regional Ministry of Ecology that monitored road cameras in real time, identified waste trucks by shape and license plate, cross-checked electronic permits, and flagged route violations—such as skipping landfills. In just three years, this system reduced illegal dumping by 44–60%, saved 75 million rubles, and issued 6,000 automated fines.

In 2023, the Russian Environmental Operator and Sberbank launched an AI satellite-monitoring platform called Geometry. This neural network scans satellite imagery of Russian territory to detect illegal landfills from space.

Now Ulan-Ude is positioning itself as an urban innovation lab. More than just cameras, this project fosters a new form of digital environmental consciousness. Drawing on federal initiatives and regional success stories, Buryatia is leading the charge for cleaner, smarter cities. The message is clear: the era of weekend cleanups is giving way to the era of algorithms.