In Russia, Fog Won’t Fool Neural Networks: They Can ‘See’ Real Wildfires
Russia is moving toward AI-driven forest protection, training neural networks to distinguish smoke from fog and identify wildfires earlier and more accurately.
AI Learns to Spot Early-Stage Wildfires
Russian forestry authorities are developing machine‑vision systems that can differentiate wildfire smoke from fog in real‑time video feeds. The core of the technology is a dataset of massive video archives that allow AI models to detect early signs of fire even in challenging weather conditions. The system reduces response time between the emergence of a hotspot and the moment fire crews receive an alert.
Drones Patrol Remote Forests
Alongside AI video analytics, Russia is deploying drone groups to monitor forests. A single operator can control multiple UAVs, making it possible to inspect remote or inaccessible areas. Specialized firefighting drones are also being developed—they can extinguish small‑scale fires of up to one hectare, helping respond quickly in regions where ground crews cannot operate.
A Digital Layer of Forest Protection
The combination of AI‑powered video surveillance and agile firefighting drones forms a mobile digital infrastructure for forest safety. This integrated approach strengthens monitoring during high‑risk fire seasons and helps safeguard remote territories where rapid response is essential.
