Accurate mapping of tree species and estimation of wood volume and biomass are important assignments of any forest inventory. However, forestry operations currently rely heavily on field data as a basis for estimating its attributes. This labour-intensive approach provides limited information and has become a costly bottleneck in completing operations. Today, remote sensing data plays a key role to characterize forests. Generation of accurate models combining a huge bunch of data requires the use of advance AI techniques that provides real time information about woods and its resources. fora has pioneered high-resolution and timely forest inventory services which combine state-of-the-art remote sensing technologies and deep learning to produce operational forest inventories that help improving the efficiency of forest management activities. Whether LiDAR, RADAR, and/or optical imagery, airborne or satellite, these sensors able to cover a large area for intensive sampling without the disadvantages inherent to labour-intensive ground sampling schemes done by field crews. However, each remote sensing solution has its own pros and cons, mainly to operate as stand-alone service. FORECAST is at the forefront of how geospatial and remote-sensing data can be harnessed to optimize safety, efficiency and productivity of forest operations. Key to FORECAST innovation is the fora proprietary calibration systems based on a double application of AI algorithms. FORECAST is the solution for forest managers and wood and paper companies, reducing the field plots to a minimum, while maintaining a high quality of information about the state of the forest at the (local) scale of individual plantations. Whether an organisation is concerned with timber, access to mills, recreation or conservation, achieving long term sustainability with an optimal return is of paramount importance for the design and implementation of effective sustainable forest management plans and forest-related policie

Forests, cornerstone of the EU economy (42% of EU land) and source of multiple social and environmental benefits, need to be managed according to the sustainability principles as stated in EU Forest Strategy. However managers lack accurate / up-to-date data to support it. Traditional forest inventories characterize forests from the ecologic and dasometric perspective; but they are expensive and typically planned on a 5-10years basis. This periodicity is often much lower than required for planning forests´ commercial or recreational activities on the basis of these data. Forest change rates demand tools able to monitor, on annual basis, the forest extension, the attributes of available timber, or the different ecosystem services emerged. MySustainableForest aims to develop a pre-commercial service and platform for forest stakeholders, compliant with open and standard interfaces, to integrate Earth Observation into the forest stakeholders’ decision making processes and operations. It will be implemented on the basis of GMV prototyped service, eoForest and will leverage on partners’ expertise on LiDAR and forest modelling. It engages relevant European public and private forest stakeholders: RAIZ (R&D branch of The Navigator Company), Croatian Forest Research Institute, Mendel University in Brno, Forest Owners Association of Navarra and Lithuania, Centre Nationale de la Propriété Forestière, European Forest Institute, and 2 innovative SMEs (MADERA+ and Föra). Its added value will be demonstrated in 6 different bioclimatic zones from Portugal, Spain, France, Croatia, Czech Rep. and Lithuania, and across a variety of management protocols and forest usages. The economic viability of the service will be assessed and the associated business model validated. As a larger implication of MySustainableForest, it is expected that End-Users optimize their operations up to 10%, participating SMEs´ headcounts increase up to 20% and GMV market share in the sector is incremented up to 10%.

EnergyGuard aims to develop, kickstart and sustain an open, green and robust Testing Experimentation Facility operating under real-world conditions to empower innovators in bringing trustworthy AI products to the energy market in a cost-effective manner. It will integrate five significant European large-scale testing and experimentation facilities that cover the full energy value chain,supported by European’s greenest HPC infrastructure (Meluxina). This includes a digital twin (DT) of the Portuguese Transmission Network (RDN), the CEDER-CIEMAT Microgrid with its Distributed Energy Resources (DERs), the Hydrogen testing platforms at CEA LITEN, CARTIF, BER and CIEMAT, a high-fidelity local DT of Riga's multi-apartment residential buildings and the Antrodoco Renewable Energy Community. This includes a wide range of elements to cover diverse AI test needs,including wind power, photovoltaic systems, hydropower plant, AEM,PEM and SO eletrolysers, fuel cells, EV charging stations, electric and public buses and battery storage systems. The facilities will be accessible to EnergyGuard end-users through a set of properly configured Digital Twins (DTs) and curated assets, including data, models, inference APIs, services, and applications through a AI development Testing environment. It will enable easy seamless access to assets from the EU ecosystem including AIOD, Data Spaces, DIHs and other TEFs; Moreover, EnergyGuard facilitates users to validate their products with an Acceptance Environment and a common open AI risks database for a wide range of cybersecurity and trustworthy AI assessments. The TEF will serve as full infrastructure to support national AI regulatory sandbox initiatives and deliver 5 pilot cases for the private and public sector. EnergyGuard will build upon a long-term, self-sustainable business model driven by a new entity, incorporating market-ready features early in the design, such as a subscription/plan framework, billing, and professional support

Carbon smart forestry under climate change (CARE4C) combines high level expertise and state of the art research in the context of carbon management in forests with advanced career building qualification by teaching, training and involving ESR's . CARE4C aims at substantially expanding knowledge about carbon sink by forest growth and carbon source by forest operations in order to enable carbon smart forestry under climate change. We trace the knowledge from understanding to modelling and application, and follow a clear dissemination strategy by training and teaching, publications in scientific journals and by involving forest related stakeholders and the public. The project builds upon a consortium that was successfully established within the Marie Curie IRSES project Climate-Fit Forests. Here, the consortium is enlarged by complementary academic and non-academic partners, and the exploratory focus is extended. The study area encompasses a broad range of climatic zones from Mediterranean to sub-boreal areas providing highly different growing conditions and landscapes differently affected by climate change. By this multilevel and multidisciplinary approach we overcome the restrictions concerning the transferability of locally and case study focused results. We plan a rather high number of secondments in order to efficiently extend the interdisciplinary network and dissemination. The project connects countries where both, integrative and segregative approaches, are prevailing in forest management. The forest types of interest include pure and mixed stands as well as complex structured close to nature forests. We track climate induced impacts on carbon sequestration on cell, organ, and tree level up to stand and landscape level. For a broad spectrum of forest types and management approaches we measure and compile information about carbon sink and source, model the carbon balance, take into account economics and derive carbon smart forest management options under climate

The initiative for Fostering DIHs for Embedding Interoperability in Cyber-Physical Systems of European SMEs (DIH4CPS) will help European enterprises overcome these innovation hurdles and establish Europe as a world leading innovator of the Fourth Industrial Revolution. DIH4CPS will create an embracing, interdisciplinary network of DIHs and solution providers, focussed on cyber-physical and embedded systems, interweaving knowledge and technologies from different domains, and connecting regional clusters with the pan-European expert pool of DIHs. Backed by the IVLab, an experienced and well-established network organisation focussed on Interoperability, DIH4CPS can innately build on an extensive existing network, add value to its existing knowledge transfer capabilities and guarantee the sustainability of the growing DIH network. DIH4CPS expands the already existing network and aims for creating an integrated platform for DIHs from different, especially digitally underdeveloped sectors and regions. A selection of eleven initially starting application experiments guarantees an outstanding funding for European SMEs and Mid-Caps right from the start and demonstrates the high dedication of the consortium to reduce the digital divide. At least ten additional experiments will take up that torch during the project and allow external companies from sectors in need to further exploit the DIH4CPS network and uplift their portfolio, especially by including (semi)-autonomy into their products and systems. DIH4CPS will not only benefit the application experiments but also the individual DIHs by significantly complementing the regional investments made. Implemented in the IVLab structure, the DIH4CPS Network will leverage and sustain its impact far beyond the project duration, creating a vibrant, overarching and cross sector one-stop-shop for collaboration between SMEs, DIHs and Tech providers.