AGRARSENSE – Smart, digitalized components and system for data-based Agriculture and Forestry Sisältöön liittyvät linkit Siirry hankkeen omalle sivulle Lisätietoa Anne Saloniemi Aikataulu 1.1.2023 -31.12.2025 YK:n kestävän kehityksen tavoitteet Koulutus Metsätalous Osaamisryhmä Tulevaisuuden biotalous Rahoituslähteet Business Finland Hankkeen tila Käynnissä Osaamiskärjet Vastuullinen metsänhoito ja puunkorjuu Tavoite AGRARSENSE will focus on developing European SoA technologies for future agricultural needs, encompassing various agricultural and forestry related challenges around them, as well as the enabling technologies of ICT infrastructure and electronics hardware that will be critical for future business and economic needs. This project drives the agenda for rapidly emerging agricultural growth in electronics, AI and automation and analytical tasks.The goal of the AGRARSENSE project is to develop sensor and decision-support technologies and enablers for smart farming with a holistic approach that is concretely demonstrated in seven use cases. These use cases in AGRARSENSE are focused on developing solutions for the following innovation problems with significant potential business impacts:– How greenhouse operations could be improved? (UC1)– How vertical farms could improve resource exchange? (UC2)– How to improve the monitoring capabilities in vineyards? (UC3)– How to increase the level of automation of agricultural robots? (UC4)– How to improve the operations and safety in forestry? (UC5) – How to reduce the impact of (or damage) organic soils? (UC6)– How to optimize the use of fertilizers? (UC6)– How to monitor and control water pollution? (UC7) Tulokset As a result, project has developed European SoA technologies for future agricultural needs, encompassing various agricultural and forestry related challenges around them, as well as the enabling technologies of ICT infrastructure and electronics hardware that will be critical for future business and economic needs.As a result of the project LUAS will develop a Virtual environment/Digital twin of a forest which can be used to train forest machine AI to be able to move autonomously in the forest.