The QuantiFarm project focusses on supporting the further deployment of digital technologies in agriculture (DATs) as key enablers for enhancing the sustainability (economic, environmental, social) performance and competitiveness of the agricultural sector. It will achieve this by establishing a framework for assessing the impact and effectiveness of DATs in agriculture and developing innovative tools, services and recommendations for farmers, advisors and policy makers. Following a multi-actor approach, QuantiFarm will build the project activities around 30 Test Cases (TCs) which span over 20 countries in 10 (of the 11) Biogeographical regions across Europe, capturing multiple geo-political and financial settings. All 30 TCs take place in commercial farms of different types, sizes, ownership and operating conditions from 7 agricultural sectors. Different aspects of these TCs will be examined in the context of different work packages (WPs). The TCs’ actors will be engaged in participatory observation activities to offer valuable input and actively support the behavioural analysis (WP1), the establishment of the Assessment Framework (WP2) and the co-design of an innovative Toolkit for farmers, advisors and policy makers (WP3). The lean multi-actor approach will be used in the testing activities to evaluate the QuantiFarm Toolkit and validate the Assessment Framework by testing the various DATs in real life conditions, across 3 iterations/growing seasons (WP4). The outcomes will be transformed into policy recommendations (WP5) and will feed the QuantiFarm DIA that will help build the capacities of farmers’ advisors in DATs. Finally, a WP on dissemination, ecosystem building and exploitation (WP6), will guarantee the wider dissemination and knowledge transfer in a multi-actor context of the outputs of the project. QuantiFarm includes 32 partners, 12 of them representing farmers and advisors.

New trends such as teleworking and e-commerce, as well as the need for a further increase of digital tools in all sectors (i.e., health, education, transportation, farming, etc.) demanded by the Covid-19 pandemic, are pointing out once again digital territorial inequalities, supply-chain disruptions and deficiencies in economic opportunities that hamper resilience and prosperity of rural communities. Accessibility and connectivity are key issues to mitigate this erosion of socio-territorial cohesion. However, identifying a common solution for equipping rural communities with increased access to services, opportunities and adequate innovation ecosystems ensuring that no one left behind is a challenging task, mainly due to the diversity of challenges and needs of different locations. In this respect, XGain fosters a sustainable, balanced and inclusive development of rural, coastal and urban areas by facilitating access to relevant stakeholders, such as municipalities, policymakers, farmers, foresters and their associations, to a comprehensive inventory of smart XG, last-mile connectivity and edge computing solutions, and of related assessment methods. The XGain overall project objective is, to deliver a Knowledge Facilitation Tool, facilitating business model development, supporting decision-making in the selection of an ecosystem of technologies, consisting of connectivity options and edge processing solutions, by following a multi-actor and practitioner-oriented approach, and by coherently assessing their socio-economic and techno-environmental effects, aiming at: increasing systemic resilience and energy efficiency; contributing to climate mitigation; and reducing the digital divides between different types of citizens, farms, sectors and regions.

OptiFish will strive to provide technological solutions that will simultaneously improve the sustainability of fisher’s operations, enhance control processes and strengthen society’s trust in their products. OptiFish will develop, test and recommend a set of innovative technologies and tools supported by artificial intelligence (AI) to provide the management, the fishing sector and the scientist with data on catch volumes, catch compositions and the fishing environment. The goal is to unlock the full potential of technologies such as electronic and genetic monitoring for automated species recognition based on AI and computer vision to reduce discards, unreported landings and unreported fishing activities, ultimately establishing a fisheries control and enforcement system fit for the digital age. The technologies are not enough alone, it is also critical to consider the combination of technologies and the integration of computer vision models, the wide range of data sources and their subsequent formats, while also addressing stakeholders needs and acceptance. This goal cannot be achieved by a single project, which is why the aim of OptiFish is to lay a solid foundation for full technological development from which other projects and initiatives can be built. The project will place a strong focus on species recognition in different fisheries equipped with distinctly different catch handling facilities and in different European sea basins. To ensure that these innovations are relevant to fisheries management, OptiFish has participation from the Norwegian Directorate of Fisheries, and has received written support from the European Fisheries Control Agency (EFCA), the Basque, Danish and Belgian Fisheries authorities.