The working hypothesis behind SmartForest is that the next leap in efficiency and environmental performance of the forest sector will be enabled by digitalization and knowledge-based management. In SmartForest a series of enabling technologies (drones, remote sensing data, sensors, machine data, robotics, blockchain, and digital twinning) are deployed in the forest sector, leading to innovations, improved efficiency, and new business models. SmartForest operates with six key applications areas, implemented as work packages, for digitalization in the forest-based value chain: (1) Forest resource information: where emerging different sources of data are combined resulting in improved continually updated forest information, (2) Precision silviculture: where cost-efficient and potentially semi-automated treatments such as precision regeneration or fertilization are developed and implemented for increased growth rates, (3) Digitally-enabled forest operations: improve production efficiency and reduce environmental impacts by applying digital tools to better plan forest harvesting, to improve machine operator performance, and ultimately to automate or semi-automate some components of forest harvesting, (4) Precision wood supply: where the value of harvested wood is maximized through optimization of sensor-generated information on wood quality throughout the supply chain, and the supply fluctuations are reduced through improved planning with new digital tools, (5) Traceability and certification: where full traceability of each log from stump to end product is enabled though application of sensors and tracking technologies and the information is utilized to improve certification procedures, and (6) The digital value chain: where new and existing digital tools and systems are connected in forming the foundation for all actors to share and access data and information, and in this way optimize the whole value chain performance.
Project leader: Rasmus Astrup
Institution: NIBIO - NORSK INSTITUTT FOR BIOØKONOMI