nvision is keen to hire an Innovation Associate (IA) to add a new line of research to its R&D strategy for elderly ADL (activities of daily living) monitoring in homes applying gas sensors. The SME has developed a solution, enSenior which is addressed to the elderly care market that uses conventional IoT sensor data like (motion, magnetic, pressure, etc.) and machine learning algorithms to monitor daily ADL and detect anomalous events. But one or more of these sensors need to be fixed per room which makes the solution more complex and costly, with further possibilities for ‘dead spots’ resulting in inaccurate detections. From our preliminary research, we have identified the potential of gas sensors to overcome these drawbacks. But our R&D team lacks the necessary expertise in gas sensors and its application for ADL monitoring. The lack of financial resources and difficulty of finding researchers with this specific knowledge and skills in the local job market is the main motivation for nvision to apply for this call. We strongly believe this innovation idea has tremendous potential to add new functionalities and reduce cost of our solution making it more competitive. According to the requirements, nvision has proposed a tailored training programme and a comprehensive career development plan for the hired IA. The IA will be completely integrated in the R&D group, sharing an office with other team members, having access to all equipment and participating in all departmental activities. The IA will perform all the tasks related to project, both technical and management as detailed in the work package descriptions, supported always by the supervisor. The IA will also acquire know-how on global market approach in the IoT industry in general and elderly care in particular. nvision is fully committed to developing the career prospects for the IA and will explore all possibilities to extend IA’s position in the company after the completion of this project.

Along the whole value chain in using data for economic purposes, guidelines and tools are required to make the business of the different stakeholders successful, and the end-users confident that none of their rights are endangered. CERTAIN addresses these needs and delivers solutions for data holders, dataspaces and AI systems providers, and AI systems deployers, which are the primary actors of the data and AI value chain. They must be compliant with applicable European regulations, must reach this compliance in a timely manner, and at reasonable cost. CERTAIN delivers guidelines and technical tools to help with compliance, to assess data quality, to measure biases in datasets, and to protect privacy. CERTAIN sets the foundation of AI certification: it translates the regulations to business terms, builds a directory of certification entities per business, develops a platform to streamline the certification process, and tools for AI system providers and certification entities so that they could respectively prepare and run a certification process. In case of security breach, not only privacy may get compromised, but also AI models may become useless and lead to extremely damageable decisions. To make sure that AI-based products are of high quality and reliability, CERTAIN develops security tools and methods, specifically suitable for dataspaces and AI systems. CERTAIN addresses the environmental footprint of the AI value chain. Innovative techniques are elaborated to reduce energy consumption when building and running AI systems. This is beneficial not only for the green deal but to reduce cost for AI stakeholders. As importantly, CERTAIN considers the end-users perspective, and provides templates and guidelines that may be used by AI systems deployers to reassure end-users on the use of their private data. The project tests its results on seven operational pilots in six different business areas, considering all the actors along the AI value chain.

In this project, leading European universities, research centers, and companies within the battery supply chain are bringing their expertise and innovations together to create the next-generation BMS platform able to overcome critical challenges limiting the performance of the existing solutions. iBattMan will incorporate novel sensors and methodologies for monitoring the State-of-Health (SOH) of the cells during operation and in charging, together with cutting-edge technologies and tools for V2X and second-life applications, and use advanced physics- and data-based models implemented on-board and on-cloud for performance evaluation, diagnosis, health management and safety evaluation tools, to trigger actions to address safety and cyber-security concerns. This will result in an innovative, modular and scalable BMS, for a wide range of vehicles, from small passenger cars to e-buses and electric trucks, with improved performance, connectivity, security and reliability to enhance battery performance and reduce total cost of ownership in EV applications and intelligent battery use for grid support and in 2nd life applications, based on a holistic design of an interoperable architecture and supported by a suite of advanced sensors and edge- and cloud-computational resources. This will represent an outstanding step forward in the EU battery development roadmap and enable accelerated market adoption of smart batteries to bring to market world-leading class Li-ion technologies to improve the cost-effectiveness, circularity, and sustainability of the EU battery industry by 2030-2035. It will support the integration of more renewables on the grid based on new concepts such as Smart Cities and Net Zero Buildings to benefit EV car manufacturers and complementary markets like urban mobility, 2nd life application for stationary storage, batteries, and battery recycling.

The primary aim of EDGE-SA is to investigate the potential suitability and applications of Systolic Arrays (SA) and Evolvable Hardware (EHW) as acceleration solutions for data processing challenges that demand extensive computation at the edge, especially crucial for resource-constrained devices. These technologies can serve as supporting mechanisms alongside existing technologies like Artificial Neural Networks (ANN). Additionally, indoor tracking of assets is considered as a real-world application context to enhance and validate the research since, at present, there is no reliable commercial solution available in the market that can deliver high accuracy.

Anxiety disorders’ diagnosis, decision and treatment processes are still uncertain and inconsistent especially in a fast-evolving real world where stressors affect people in different ways. SMILE aims to improve the quality of mental health management and ensure affordable services by sharing information, providing scalable digital tools, and ensuring personalized decision-making and evidence-based interventions in an effective way. To achieve these goals, SMILE will develop mainly Open Knowledge Platform (OKP) and interactive gamification tools. OKP will bring together healthcare professionals, scientists, policymakers, businesses, and citizens to co-design effective decision strategies and unlock access to meaningful knowledge. Gamification will provide self-assessment, learning, and self-care services for young people to develop thinking, coping, and doing skills. Hence, SMILE will be able to integrate and analysis at least 7 different diagnostic data from clinical data to daily living parameters. Also, SMILE will assist primarily clinicians and help patients through 3 decision-making tools. The analytics and predictive tools will support practitioners in understanding the associations between risk factors, and anxiety, and recommending interventions in a personalized way. The SMILE digital tools and services will be implemented and validated in eight real-life strategic case studies, in 7 different European countries: UK, Germany, Cyprus, Poland, Slovenia, Spain and Italy, to reach TRL 7. Also, a systematic upscaling method will be deployed to sustain our program and ensure the continuity in the post-project. SMILE will deliver durable legal, socio-economic, gender and environmental values for the benefit of healthcare professionals, patients, EU SMEs and society at large. Finally, SMILE has strong multidisciplinary skills and is composed of one leading research center, 5 SMEs, 3 pilot centers, 4 public universities, and 1 policymaker from 9 European countries.