R-Map aims to analyze the impact of remote working arrangements (RWAs) on the disparities between urban and rural regions in Europe. The project bases its research on the premise that understanding and shaping the trends related to the emergence of RWAs provides an opportunity to bridge the urban-rural divide affecting its multiple facets. To achieve its goals, R-Map will produce an Integrated Impact Assessment Framework (powered by the R-Map model) that will allow the assessment of individual, social, economic, environmental and spatial impacts of RWAs. A visualization platform will be developed leveraging the R-Map model to provide visualization and interactive services allowing decision-makers to monitor and assess how remote work arrangements affect people, communities, space, economy, and environment in urban and rural regions. The developed tools will be applied at local level to monitor and assess current remote working trends across six representative use-cases in the EU and the AC, in regions within Greece, United Kingdom, Italy, Turkey, Netherlands-Germany, Austria-Switzerland (two cross-border cases). Using scenario building and forecasting methodologies, R-Map will move on to explore the potential future impact of remote work in these regions for the next 5-10 years and formulate policy recommendations on how to create environments conducive to remote work, that are tailored to the needs of local governments in both urban and rural settings. Cross-regional exchanges between stakeholders and policy roundtables will help move beyond the regional focus ensuring the replication of results across areas with different characteristics in Europe and beyond. By taking a comprehensive approach to research on RWAs, R-Map addresses the role and the needs of policymakers, employers, workers, researchers, and civil society, providing capacity to urban and rural regions to seize the opportunities and cope with the challenges brought by remote work.

MANOLO will deliver a complete stack of trustworthy algorithms and tools to help AI systems reach better efficiency and seamless optimization in their operations, resources and data required to train, deploy and run high-quality and lighter AI models in both centralised and cloud-edge distributed environments. It will push the state of the art in the development of a collection of complementary algorithms for training, understanding, compressing and optimising machine learning models by advancing research in the areas of: model compression, meta-learning (few-shot learning), domain adaptation, frugal neural network search and growth and neuromorphic models. Novel dynamic algorithms for data/energy efficient and policy-compliance allocation of AI tasks to assets and resources in the cloud-edge continuum will be designed, allowing for trustworthy widespread deployment. To support these activities a data management framework for distributed tracking of assets and their provenance (data, models, algorithms) and a benchmark system to monitor, evaluate and compare new AI algorithms and model deployments will be developed. Trustworthiness evaluation mechanisms will be embedded at its core for explainability, robustness and security of models while using the Z-Inspection methodology for TrustworthyAI assesment, helping AI systems conform to the new AI Act regulation. MANOLO will be deployed as a toolset and tested in lab environments via Use Cases with different distributed AI paradigms within cloud-edge continuum settings; it will be validated in verticals such as health, manufacturing, and telecommunications aligned with ADRA identified market opportunities, and with a granular set of embedded devices covering robotics, smartphones, IoT as well as using Neuromorphic chips. MANOLO will integrate with ongoing projects at EU level developing the next operating system for cloud-edge continuum, while promoting its sustainability via the AI-on-demand platform and EU portals.

RIBES will address the need to enhance the uptake of biobased innovations through pioneering governance and business models developed on the convergence of the circular bioeconomy, social innovation and rural development, thus contributing to the shift from a linear to a circular economy in 9 European regions lagging in innovation. Project activities will focus on specific sub-national levels but will also encompass proactive dissemination and replication at the country level. Participating regions have been selected based on various socio-economic indicators and data concerning the characteristics of the agricultural and biobased sectors, demographics, innovation capacity, etc. RIBES will perform an in-depth multidisciplinary assessment of regional bioeconomy ecosystems and research possible correlations between the socio-economic trends, innovation bottlenecks and the role of the primary sector. RIBES will create a significant impact by delivering innovative and tailored governance solutions and business models capable of fostering grass-rooted circular bioeconomy value chains, with particular attention devoted to the advanced sustainability of regional inclusive biobased entrepreneurship solutions, thus contributing to strengthening rural development and innovation in participating regions. RIBES will implement 9 local Multi-actor Transformative Forums (MTFs) based on the Living Lab and Open Innovation concepts to address complex societal challenges and problems by putting stakeholder participation and deliberation processes at the centre, aiming at systemic transformative change (instead of only addressing symptoms) in the three pillars of technological, social and economic innovation to co-create tailored business and governance models.

REHUBS addresses the issues of climate vulnerability in rural areas and small to medium-sized communities, which are particularly susceptible to climate risks such as droughts, heatwaves, wildfires, floods, and biodiversity loss. REHUBS’ goal is to enhance climate resiliency of these areas by developing an integrated framework of adaptation solutions, advanced digital tools, and participatory approaches, tailored to the specific needs of the rural communities. The project will design, implement and validate a Climate Risk Assessment model, an Advanced Early Warning System, Flood and Drought Modelling tools, Smart Irrigation Systems, a Circular Water Recovery Treatment, a Rapid Wildfire Detection System, as well as a Risk Assessment and Adaptation Platform that will recommend a list of cost-effective nature based solutions (NBS). REHUBS will promote knowledge transfer, enhance the adaptation capacity of local authorities, and upskill local actors through an online academy, an AI support chatbot and through fostering stakeholder collaboration through the project’s established Rural Micro Hubs (RMHs). The solutions developed in REHUBS will be implemented and validated across four Demonstration Cases, with replication in three additional Replication Cases, ensuring that they, not only address immediate climate risks, but also build long-term resilience by integrating climate adaptation strategies into local governance frameworks. Additionally, the project will introduce innovative financial instruments to support the sustainable implementation of these solutions, ensuring both their cost-effectiveness and replicability across different European regions. The project's outcomes will contribute significantly to enhancing the adaptive capacity of rural communities, supporting EU climate goals, and ensuring socio-economic and environmental sustainability in regions facing critical climate challenges.

INSPIRE project supports sustainable and inclusive development of European rural areas by promoting social wellbeing and inclusion of rural dwellers and vulnerable groups. In particular, the project contributes to advancing in a multi-dimensional way the concept of social inclusion in rural areas, and supports the access to high-quality social services by rural citizens through a series of awareness-raising, capacity-building, and pilot deployment activities that focus on social entrepreneurship in a set of 7 different pilot territories (e.g., coastal, rural, peri-urban, mountainous). To realise its objectives, the project provides a novel territorial typology of rural areas, sets up and operationalises "Smart Village labs", and enhances governance frameworks and informed policy making through E-Democracy and user-innovation techniques, to eventually deliver a dedicated Rural Social Inclusion Policy Dashboard.