AAI Labs completes model development for smart forests

AAI Labs, together with the BONO SIA companies group, is working to modernise the timber sector and has completed the development of a set of models for smart forestry. Their integration into forest management and wood processing businesses will increase the efficiency and competitiveness of supply chains.

Thanks to artificial intelligence and computer vision technologies, models are capable of timber volume estimation, defect detection, origin identification, forecasting of forest health, timber supply and demand. Advanced algorithms are used to ensure accurate and fast results upon the input of required data by the user.

The models can distinguish between log and sawn timber piles, and determine their number and volume from the images provided. The technological solutions developed can detect wood defects such as splits, rot, and plant diseases. This allows for optimising the use of wood and reducing waste while increasing the overall quality and value.

The analysis of satellite imagery can be used to assess the state of the forest by identifying the type of forest cover (deciduous, coniferous), volume and other environmental parameters to implement sustainable forest management strategies.

The developed solutions are also capable of forecasting wood supply and demand using data on forest resources, market trends and climate change impacts. This information will help foresters, timber buyers and processors to optimise their supply chains.

"This is a major step forward in technological progress in the forestry sector. The product we have developed allows foresters to obtain more accurate information on timber volumes and quality, reducing the likelihood of human error and enabling them to react quickly to market changes", said Aistis Raudys, CEO of AAI Labs.

The AAI Labs and BONO SIA team hopes that their technological solutions will contribute to the promotion of environmental awareness and better forest management practices, and reduce illegal logging. The developers of the models expect such technology to become a basis for the sustainable development of the forestry sector, creating new business opportunities.