Russian Oil and Gas Companies Turn to Izhevsk-Built Drones for Aerial Monitoring
ZALA unmanned aerial vehicles manufactured in Izhevsk are now equipped with new onboard AI systems. These systems analyze data from video cameras and thermal imagers in real time and automatically detect anomalies at oil and gas facilities.
An Eye in the Sky
AI-based machine vision algorithms deployed on the unmanned aerial vehicles are used for automated analysis of visual and thermal data. The drones operate in both daytime and nighttime modes. Data processing takes place in real time, with up to 70 percent of events detected and classified without operator involvement, significantly reducing response time to abnormal or emergency situations.
Izhevsk-built drones are currently in operation across 65 regions of Russia. The Izhevsk manufacturing facility has announced plans to supply 200 ZALA T-16 and ZALA T-20 unmanned aerial vehicles, along with mobile laboratories, to one of the largest enterprises responsible for safeguarding Russia’s fuel and energy complex. The customer has not been disclosed. In addition to the aircraft themselves, the contract includes mobile laboratories mounted on high-mobility off-road vehicles.
The UAVs are equipped with IRRA technology, an integrated hardware and software system. The platform automatically tags detected violations and transmits information about potential threats to a ground-based control station for further assessment and action.
Aerial Support for Industrial Monitoring
Over the past decade, unmanned aerial vehicles have been widely adopted in the mining sector. A broad range of critical tasks has been delegated to UAVs, from mineral exploration to post-industrial land reclamation. Drones have become standard tools for aeromagnetic surveys, mine surveying operations, and tailings dam monitoring.
UAV deployment improves the efficiency and responsiveness of monitoring, reduces operational costs and risks, and significantly enhances the quality of real-time data. These systems are well suited for generating digital terrain models, mapping geological structures, and monitoring slope stability and open-pit conditions. Many industrial operators report high accuracy and rapid data acquisition, supporting more effective planning and higher safety standards in production processes.
Their rapid adoption is also driven by labor and cost savings. Tasks that previously required teams of specialists from multiple disciplines can now be handled by a single drone operator.
Izhevsk Expands Production Capacity
In 2026, the Udmurt Republic, recognized as Russia’s leading region for UAV production, will receive approximately 1 billion rubles (around $12 million) under a national development program. The funding will be used to establish a research and manufacturing center for unmanned aviation systems at the Kalashnikov Izhevsk State Technical University. A major focus of the initiative will be training highly qualified specialists to support long-term industrial and technological objectives.
It is already clear that Russia is developing these capabilities not only for domestic use. AI-driven automated monitoring systems are likely to attract interest from international oil and gas companies operating extensive infrastructure networks in regions such as the Middle East, Latin America, and Africa. This technological head start creates a foundation for strengthening Russia’s position in the intelligent monitoring market, competing with Western solutions through more competitive pricing and adaptation to local operating conditions.
Drawing Conclusions
The technology has strong potential for application beyond oil and gas, including electric power grids and municipal infrastructure. To achieve maximum impact, AI-based monitoring must be integrated with industrial Internet of Things platforms and industrial safety systems. A longer-term objective is the development of autonomous response services that move beyond reporting toward automated corrective actions.
In extractive industries, both mining and oil and gas production, unmanned systems are increasingly being deployed for routine and mission-critical tasks. These trends lay the technological groundwork for deeper integration of AI analytics and automated decision-making, which could significantly improve efficiency and asset monitoring across the sector.
The deployment of ZALA UAVs with AI-powered monitoring, developed through collaboration between domestic enterprises, represents a practical application of Russian intelligent technologies to enhance infrastructure security. This aligns with national priorities in digital transformation and technological sovereignty.
