WoodQAI – artificial intelligence for wood quality

Artificial intelligence meets forestry: WoodQAI is a research project that rethinks how wood quality is assessed. The goal is an app that analyses logs from a photo and detects quality features such as rot or knottiness — so private forest owners and businesses can judge the value of their timber right where it lies.

Why WoodQAI?

Forests and the raw material wood are central levers for a climate-neutral economy. Yet for private forest owners — the majority in North Rhine-Westphalia — it is often hard to judge the quality of their wood. That assessment, however, is a key factor in the price it can fetch.

This is exactly where WoodQAI comes in: using machine-learning methods, the end-grain (cut) surfaces of logs are analysed to detect the features that directly drive the quality grade. The project starts with beech — the most important hardwood by volume — and later extends the results to further species such as spruce or oak.

Right in the forest — even offline

The quality assessment runs directly on the smartphone, on site. Because there is no internet connection everywhere in the forest, the AI algorithms also deliver a result offline. Once a connection is available again, assessed images can — with the user’s consent — be contributed via a secure data space for re-training. A planned citizen-science app with gamification elements also invites the public to help gather data.

Consortium & funding

WoodQAI is a joint project led by the RIF Institute for Research and Transfer together with Forstify GmbH and SNAP GmbH. Associated partners are Hegener-Hachmann GmbH & Co. KG, the State Enterprise for Forestry and Timber NRW and the Faculty of Forest Sciences and Forest Ecology at the University of Göttingen.

The project runs from 1 July 2025 to 30 June 2028 and is funded under the ERDF/JTF programme North Rhine-Westphalia 2021–2027.