PREVENT improves upscaling of primary interventions for weight control management during childhood and adolescence to reduce cancer risks in adulthood. This relies on current evidence that relates excess body weight with increased cancer risk. Towards this end, PREVENT applies a series of implementation research actions in the following directions. First, it identifies barriers to current interventions and policies preventing them from upscaling to different geographical, socio-economic, and cultural settings. Then, it introduces new multi-actor and context-aware interventions along with new user engagement strategies to face the current upscaling bottlenecks; multi-actor in the sense that they target different types of users (e.g., students, family, educators, policymakers) and context-aware in the sense that PREVENT interventions are tailored to the specific implementation places (class, canteen, sports fields, labs, outside school). The PREVENT new policies are adapted, piloted, and scaled up within the schools’ communities of three European countries facing different epidemiological settings on childhood obesity, geographic, socio-economic and cultural attributes. The pilots are designed to be holistic end-to-end ecosystems, including users, medical professionals, policymakers, public authorities, and civil communities. They focus on the whole school communities of Greece, Sweden, and Spain-Catalonia, that is, PREVENT outreach to more than 3.3 million students, required for guideline provisioning, large-scale implementation, multi-parameter assessment, and scaling-up. Co-creation, active behavioral change, self-evaluation through user empowerment, motivational interviewing, social innovation, digital-assistive engagement, health apps, and multi-domain assessment are implementation research aspects of PREVENT to advance user acceptability and compatibility with existing policies, and thus improve sustainability and upscaling. This action is part of the Cancer Mission cluster of projects on "Prevention and Early Detection".

HERON aims to develop an integrated automated system to perform maintenance and upgrading roadworks, such as sealing cracks, patching potholes, asphalt rejuvenation, autonomous replacement of CUD elements and painting markings, but also supporting the pre/post-intervention phase including visual inspections and dispensing and removing traffic cones in an automated and controlled manner. The HERON system consists of: i) autonomous ground robotic vehicle that will be supported by autonomous drones to coordinate maintenance works and the pre-/post- intervention phase; ii) various robotic equipment, including sensors and actuators (e.g., tools for cut and fill, surface material placement and compaction, modular components installation, laser scanners for 3D mapping) placed on the main vehicle; iii) sensing interface installed both to the robotic platform and to the Road Infrastructures (RI) to allow improved monitoring (situational awareness) of the structural, functional and RI’s and markings’ conditions; iv) the control software that interconnects the sensing interface with the actuating robotic equipment; v) Augmented Reality (AR) visualization tools that enable the robotic system to see in detail surface defects and markings under survey; vi) Artificial Intelligence/AI-based toolkits that will act as the middleware of a twofold role for: a) optimally coordinating the road maintenance/upgrading workflows and b) intelligent processing of distributed data coming from the vehicle and the infrastructure sensors for safe operations and not disruption of other routine operations or traffic flows; and vii) integrate all data in an enhanced visualisation user interface supporting decisions and viii) communication modules to allow for Vehicle-to-Infrastructure/-Everything (V2I/X) data exchange for predictive maintenance and increase users safety. HERON aims to reduce fatal accidents, maintenance costs, traffic disruptions, thus increasing the network capacity and efficiency.

Intangible Cultural Heritage (ICH) content means "the practices, representations, expressions, knowledge, skills – as well as the instruments, objects, artefacts and cultural spaces associated therewith". Although, ICH content, especially traditional folklore performing arts, is commonly deemed worthy of preservation by UNESCO (Convention for the Safeguarding of ICH) and the EU Treaty, most of the current research efforts are on the focus is on tangible cultural assets, while the ICH content has been overlooked. The primary difficulty stems by the complex structure of ICH, its dynamic nature, the interaction among the objects and the environment, as well as emotional elements (e.g., the way of expression and dancers' style). TERPSICHORE aims to study, analyse, design, research, train, implement and validate an innovative framework for affordable digitization, modelling, archiving, e-preservation and presentation of ICH content related to folk dances, in a wide range of users (dance professionals, dance teachers, creative industries and general public) . The project targets at integrating the latest innovative results of photogrammetry, computer vision, semantic technologies, time evolved modeling, combined with the story telling and folklore choreography. An important output of the project will be a Web based cultural server/viewer with the purpose to allow user’s interaction, visualization, interface with existing cultural libraries (EUROPEANA) and enrichment functionalities to result in virtual surrogates and media application scenarios that release the potential economic impact of the ICH. The final product will support a set of services such as virtual/augmented reality, social media, interactive maps, presentation and learning of European Folk dances with tremendous impact on the European society, culture and tourism

Eco-Bot aims to utilize recent advances in chatbot tools and advanced signal processing (i.e. energy disaggregation) using low-resolution smart meter-type data with the goal of changing their behaviour towards energy efficiency. Eco-Bot targets to a personalized virtual energy assistant to deliver information on itemized (appliance-level) energy usage through a chat-bot tool. The "chat-bot" functionality will be use an attractive frontend interface, permitting seamless communication in a more natural and interactive way than a traditional mobile application. This way, Eco-Bot aims to achieve a higher level of engagement with consumers than previous efforts (i.e. serious games, gamification, competitions or other interactive ICT), by adding a more engaging form of interaction with existing platforms that has been proven in different market settings. The proposed system considers knowledge of the delivered multi-factorial models, including rebound-effects, as a result of the baseline research on both European and International activities. Then, based on advanced ICT, such as knowledge engineering, machine learning, expert systems, the project transforms the multi-factorial models for energy reduction to interactive, personalized and targeted recommendations to consumers on how to save energy. Eco-Bot uses also existing NILM, e.g. energy disaggregation methods, and data analytics to break down consumption to the appliance level, where this is possible (smart meters at reasonable granularity, adequate number of information collected) so as to make consumers aware of their most energy-consuming devices. The project will demonstrate the system in three different use cases, each one representing a different business model (B2B / B2B2C /B2C). We aim to validate our system across real and diverse conditions such as socio-cultural, environmental, demographic, climate and consumption, so as to draw concrete conclusions regarding performance, effectiveness, affordability, etc.