Synthetic digital twin for a computer vision precision forestry

Purpose and goal:

The project aims to develop a platform for an end-to-end AI for forest analyses and synthetic digital twins of the forest. This creates the prerequisites for the internationalization of an end-to-end AI for high-resolution forest data analysis for needs-based uses. Expected results and effects:

The project is groundbreaking and contributes to knowledge that was previously lacking about how synthetic data generation can be used to build applications in modern forestry. Projects will consider the granularity between different tree species and be able to create realistic forests.

The value is that the forest industry can evaluate between optimizing to secure higher economic profitability while setting aside forest for carbon sequestration, securing carbon sinks in wood for industry, increasing biological diversity, and assisting with nature experiences for society. Approach and implementation:

Arboair finances its part of the project in addition to the part financed by Vinnova. Other parties will finance their costs through its own funds. The owner of the need believes in the idea and the solution and sees great potential and therefore invests time, data, and money in the project.