WoodQAI: project meeting & workshop at Hegener-Hachmann

The WoodQAI research project explores how AI-based methods can support the quality grading of logs from digital image data. In late April 2026 the project partners met at associated partner Hegener-Hachmann in the Sauerland — with a clear focus on practice.

AI-based wood-quality assessment in practice

Assessing wood quality is a central step in the forestry value chain. With log piles in particular, the question is how to capture the relevant quality features reliably, transparently and as close to practice as possible.

At the status meeting, besides the project partners RIF, Forstify and SNAP, project agency Jülich (PtJ) and associated partner Hegener-Hachmann also took part. The focus was on the work and results so far — from capturing suitable image data and deriving relevant wood features to AI-based feature recognition and the technical implementation on mobile devices.

Hands-on insight from the sawmill

A particular highlight was the tour of the sawmill. On site, the participants could follow the processes of timber intake, sorting and further processing, and deepen their understanding of the requirements from a practical point of view. It became clear how demanding a robust quality assessment of logs can be — and what potential digital tools offer for a more objective and efficient evaluation.

The participants rated the status meeting and the exchange as very successful. Important impulses were gained for the coming project phases, to develop the AI-based wood-quality assessment further towards a practical application.