A NETWORK of solar-powered gas sensors equipped with AI has detected a wildfire in Lebanon within 30 minutes of ignition, allowing the blaze to be extinguished with minimal damage.

The Silvanet system, developed by Germany’s Dryad, employs AI-enabled gas sensors within a large-scale, solar-powered mesh network embedded in forested areas. The technology focuses on early detection to prevent wildfires from spreading out of control.

Comprising 139,000 hectares – roughly 13 per cent of its land area – Lebanon’s forests are increasingly at risk from wildfires due to climate change. Extended periods of drought pose a threat, elevating the risk of fires in higher-altitude regions that historically experienced fewer wildfires. Additionally, pest outbreaks are contributing to the desiccation of trees before the onset of the fire season. Lebanon’s renowned cedars, along with junipers and firs, are among the endangered forest ecosystems.

Mada – a telecoms operator in the Middle East and Africa – had deployed Silvanet at a pilot site at Deir Mar Moussa in central Lebanon. Deployed since January 2023, the site features 91 sensors and two gateways, covering a 78-hectare area.

On December 11 2023, Silvanet flagged a small illegal fire within 30 minutes. The system detected a change in air composition through the Bosch BME688 gas sensor.

Subsequent gas scans identified hydrogen, carbon monoxide, and volatile organic compounds (VOCs). Silvanet’s AI then predicted a 70 per cent probability of smoke at 10:33 am, triggering an alert to the customer.