AI-based Harvester Operator Support

Purpose and goal:

The goal of the project is to further develop and evaluate advanced domain-specific AI functionality that creates a rich digital representation of a forest environment in real time based on sensors mounted on a forest machine.

The aim is to enable a new generation of operator support systems for forestry machines. Such systems facilitate the implementation of a wide range of precise forest management methods, including those that favor the forest´s carbon dioxide absorption, the preservation of biodiversity, and that the climate benefit and value of each felled tree is maximized.

Expected results and effects:

The next generation of operator support systems for forest machines creates a better working environment for operators, and enables increased goal fulfillment, precision and local adaptation in forestry. The long-term effect of this is increased growth (potential ~15% in the Nordic countries), as well as completely new opportunities to make local adaptations for the preservation of biological diversity.

Approach and implementation:

The project consortium consists of selected private actors and academic institutions with complementary competencies and project functions. The technical development work is led by NFA, with support from CIT and BOID. Södra and Sveaskog will provide machines and test drivers, as well as prerequisites for test and evaluation activities, which in turn are led by SLU and Skogforsk.