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Testing of traceability and quality assessment with image analysis/AI using a harvester as platform.

Reference number
Coordinator Tracy of Sweden AB
Funding from Vinnova SEK 1 410 000
Project duration November 2024 - April 2026
Status Ongoing
Venture Advanced digitalization - Enabling technologies
Call Test and demo of advanced digitization in a real environment

Purpose and goal

The purpose of the project is to further develop and test services that promote digitization in forestry. We use the database - Tracy Timber Cloud (roughly 6.5 million images) which was built up during the previous PiiA project. Quality characteristics are analyzed that affect quality and AI is trained to increase accuracy. As quality algorithms emerge, it is tested and evaluated in sawmills and during felling. End results is an installation at various harvester and aggregate manufacturers.

Expected effects and result

The project enables traceability/quality assessment of timber with image analysis/AI which promotes advanced digitalization within our own and other industries connected to the forest. The project leads to prototypes and pilot installations that open up new applications and development tracks. Our algorithm development platform, starting from an industry´s raw material, stimulates other industries to use algorithm and our algorithm development platform for the quality of their raw materials.

Planned approach and implementation

Our project runs 2024-11-01 - 2026-06-30 and includes a system-oriented approach and draws knowledge from several disciplines to build a system with a higher degree of autonomy that on different way can be applied within Swedish forestry/industry. The system can act autonomously in the market and is reinforced by reliable and smart built-in models. With our partners, we can further develop and test an efficient computer architecture for machine intelligence in embedded systems.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 21 November 2024

Reference number 2024-02459