Khabarovsk Scientists Develop AI-Driven System to Protect Forests
The system will combine communications infrastructure, software, analytics, and AI to detect and respond to wildfires
Researchers at Pacific National University in Khabarovsk, Khabarovsk Krai, Russia are developing an intelligent system designed to forecast, detect, and respond rapidly to landscape fires. The project is backed by the federal program Prioritet-2030 (Priority 2030 program). According to project lead Aleksandr Abuzov, director of the university’s Polytechnic Institute, the system will include a drone platform—but not a conventional one.
Protecting All Natural Areas
The project is a full-stack system that integrates communications networks, software, analytics tools, and AI components. It is designed to protect all natural areas across Khabarovsk Krai, including agricultural land and suburban forests.
The platform includes a firefighting UAV for containing outbreaks, an autonomous telecommunications unit, and a neural network system for detecting and analyzing fires. Small-batch production of drones is already underway, and a final prototype has been tested in real-world conditions. The data transmission network for remote areas has been developed, and teams are now building neural network algorithms to predict fires.
Response, Forecasting, and Control
Abuzov said the system’s key difference from existing solutions is its ability not just to detect fires, but to respond in real time, predict outbreaks, and automate firefighting operations. The regional Ministry of Forestry and Timber Processing has expressed interest in the project and is prepared to deploy it within forest protection services.
In 2026, more than 660 million rubles ($~7 million) were allocated in the region for forest protection, conservation, and reforestation efforts, including the purchase of additional drones.
Earlier we reported that systems for predicting floods and wildfires were developed in Krasnoyarsk.
