Pilot programme to roll out wildfire detection IoT network

Environmental IoT startup Dryad Networks has announced a pilot program for its ultra-early wildfire detection system

IoT network developer Dryad in Germany is looking to partner with up to ten forest owners to validate its solution at scale in areas of the world plagued by wildfires including the Americas, Europe, Indonesia and Australia.

Forestry businesses interested in applying for the pilot program need to complete a short application form by 30 September. Selection criteria includes: a minimum potential deployment size of at least ten thousand hectares; a focus on sustainable forestry management practices; and a team willing to help deploy the sensors in forests, guided by Dryad’s experts.

Dryad’s Silvanet solar-powered mesh network is based on the LoRa low power wide area network and provides public and private forest owners with an affordable and easy-to-deploy solution for tackling wildfires in under 60 minutes at the initial smoldering stage. The first of several pilots started in Germany in August 2021 following the first live demonstration of the technology in action.

“The devastating impact on the climate and on forest owners’ bottom lines of the wildfires burning across the world from Canada and California to Turkey and Greece underlines the requirement for a new approach that detects wildfires at the smoldering stage before they wreak havoc,” said Carsten Brinkschulte, CEO and co-founder of Dryad Networks. “With the first pilot deployments of our Silvanet solution already underway, we are now scanning the globe for like-minded forestry estates to partner with us on a game-changing pilot program to digitize forests, help combat wildfires, and protect the natural world and forest owners’ revenues."

Dryad’s future plans include helping forest managers to optimize the health and growth of the forest, and improve productivity and profits using data-driven decision tools. This will entail adding third-party LoRaWAN-compatible sensors to Silvanet, enabling the system to collect and analyze data on soil moisture, tree growth and the surrounding microclimate.