The DiGeBaSt project, funded by the State Forest Administration of Baden‑Württemberg (grant 02WDG013A), ran from 1 April 2021 to 30 June 2023. Its aim was to create a marker‑free traceability system for round‑wood from felling to the sawmill. Six work packages guided the effort: project management, requirement specification, development of a fingerprint method for tree trunks, system integration into forest machines and the sawmill, field demonstration, and knowledge transfer. The project team held regular digital meetings and a large in‑person partner meeting at the Kloster Bebenhausen headquarters. All scheduled milestones were met, except the digitalisation of the forestry process, which could not be finished because the software vendor did not grant access to raw image data. The project was extended by three months to accommodate hardware delivery delays that pushed the experimental schedule back.

Technically, the core achievement was the creation of a reliable fingerprinting system that can recognise individual tree trunks without physical labels. Three distinct reading devices were designed and built: an integrated reader mounted on the feller (Vollernter), a reader installed in the sawmill, and a handheld reader that replaced an initial smartphone app. The smartphone approach was abandoned because, under real‑world lighting, the contrast was insufficient and the resolution too low for accurate identification. The handheld reader, however, proved robust and was used throughout the project.

Integration of the reader into the feller involved overcoming startup challenges, but the system operated reliably during trials. In the sawmill, initial difficulties arose from flying sawdust, yet the reader was eventually installed successfully and delivered correct data. The sawmill installation comprised two cameras positioned about one metre from the bark surface, each with a pixel resolution of 158 µm before the cross‑cut and 182 µm after. The cameras were housed in a Rittal‑AX wall cabinet, equipped with two Smart Vision XR‑256‑530‑14 laser pointers and an AVT Manta G‑2460B camera with a Ricoh FL‑BC1618‑9M lens. A Sick WTT12L‑B2531 light barrier was also used. Both readers were connected to computers running AVT Vimba Viewer, and remote operation was enabled via TeamViewer.

Field trials confirmed that the fingerprint system could re‑identify individual trunks from the feller to the sawmill. The reported re‑identification rate was 9 %. While the exact figure is incomplete in the report, it indicates that the system achieved a measurable level of accuracy. The project also produced a digital twin specification for the forestry process, though full integration was not achieved due to the software access issue.

Overall, the DiGeBaSt project delivered a functional, marker‑free traceability solution for round‑wood, demonstrated through successful integration into both felling equipment and sawmill operations. The collaboration among the State Forest Administration, technical partners, and equipment suppliers was smooth, with clear communication and adherence to deadlines. The extended timeline allowed the team to resolve hardware and integration challenges, ensuring that the final system met the project’s scientific and practical objectives.