Next generation enablers, such as IoT, AI and cloud computing, open new opportunities to deal with world’s current and future societal, environmental, and economic challenges. However, they come with significant data management challenges. According to IDC, the total amount of data generated only by connected devices will exceed 40 trillion gigabytes by 2025. In most of the current systems, data storage and analysis happen on centralized locations on the cloud. This is pushing network capacity to its limits. Furthermore, centralized storage and processing lead to single point of failure situations, which are critically inefficient in case of disasters and crisis. Our world is continuously living natural disasters, health crisis, climate change and security threats that show the importance of resilient and energy-efficient information systems. COGNIFOG targets those challenges and proposes to build a Cognitive Fog Framework to: (i) reduce energy consumption and latency in next generation IT systems by reducing the network traffic, by analysing data at the edge in a distributed manner, closer to where they are generated, rather than routing them through the communication networks to a data center; (ii) reduce OPEX and faster service provisioning by providing a cognitive, self-adaptive framework with minimum or no human intervention, with dynamic provisioning of computing, storage and networking resources along the far-edge-to-edge-to-cloud path; (iii) ensure European leadership by providing an open interoperable framework with open APIs for application developers to rapidly create and deploy applications benefiting the edge-cloud continuum on top of heterogenous IoT/IT systems. COGNIFOG will validate project results in three representative application domains: critical collaboration missions, smart health and smart industry. With a consortium of 12 European partners, leaders in their domains, COGNIFOG will be a cornerstone in the cognitive fog computing domain

WorkingAge will use innovative HCI methods (augmented reality, virtual reality, gesture/voice recognition and eye tracking) to measure the user emotional/cognitive/health state and create communication paths. At the same time with the use of IoT sensors will be able to detect environmental conditions. The purpose is to promote healthy habits of users in their working environment and daily living activities in order to improve their working and living conditions. By studying the profile of the >50 (Year old) workers and the working place requirements in three different working environments (Office, Driving and Manufacturing), both profiles (user and environment) will be considered. Information obtained will be used for the creation of interventions that will lead to healthy aging inside and outside the working environment. WorkingAge will test and validate an integrated solution that will learn the user’s behaviour, health data and preferences and through continue data collection and analysis will interact naturally with the user. This innovative system will provide workers assistance in their everyday routine in the form of reminders, risks avoidance and recommendations. In this way the WorkingAge project will create a sustainable and scalable product that will empower their user's easing their life by attenuating the impact of aging in their autonomy, work conditions, health and well-being.

HosmartAI will create a common open Integration Platform with the necessary tools to facilitate and measure the benefits of integrating digital technologies (robotics and AI) in the healthcare system. A central hub will offer multi-faceted lasting functionalities (Marketplace, Co-creation space, Benchmarking) to healthcare stakeholders, combined with a collection of methods, tools and solutions to integrate and deploy AI-enabled solutions. The Benchmarking tool will promote the adoption in new settings, while enabling a meeting place for technology providers and end-users. Eight Large-Scale Pilots will implement and evaluate improvements in medical diagnosis, surgical interventions, prevention and treatment of diseases, and support for rehabilitation and long-term care in several Hospital and care settings. The project will target different medical aspects or manifestations such as Cancer (Pilot #1, #2 and #8); Gastrointestinal (GI) disorders (Pilot #1); Cardiovascular diseases (Pilot #1, #4, #5 and #7); Thoracic Disorders (Pilot #5); Neurological diseases (Pilot #3); Elderly Care and Neuropsychological Rehabilitation (Pilot #6); Fetal Growth Restriction (FGR) and Prematurity (Pilot #1). To ensure a user-centred approach, harmonization in the process (e.g. regarding ethical aspects, standardization, and robustness both from a technical and social and healthcare perspective), the living lab methodology will be employed. HosmartAI will identify the appropriate instruments (KPI) that measure efficiency without undermining access or quality of care. Liaison and co-operation activities with relevant stakeholders and open calls will enable ecosystem building and industrial clustering. HosmartAI brings together a consortium of leading organizations (3 large enterprises, 8 SMEs, 5 hospitals, 4 universities, 2 research centres and 2 associations) along with several more committed organizations (Letters of Support provided).

During the last decades, overweight & obesity rates have reached epidemic proportions across EU. Prevalence in childhood is particularly alarming, resulting in psychological impacts & increased risks for NCDs. However, although obesity-related research has provided interesting results, several issues arise due to the lack of meta-reviews & the nature of data collected. To address this, Bio-Streams aims on supporting the optimal use (and re-use) of health data (e.g. biological, demographic, epigenetic, etc.) to generate metadata/knowledge and provide new evidences, methodologies & tools for: a) creating and deploying the Bio-Streams Biobank that will act as a scientific platform for research in obesity and better diagnostic and therapeutic approaches;b) understanding the transition from metabolically healthy to unhealthy, preventing under age obesity; c) designing better strategies to educate & empower young citizens for weight self-management; d) coordinating authorities & policy makers to develop cross-sectoral solutions for health promotion & under age obesity prevention. Specifically, Bio-Streams delivers a dedicated under age obesity biobank providing real-world health data (including biospecimens, anthropometrics, behavioural and cost data) from retrospective and prospective sources, while taking into account efficient data harmonisation and standardisation principles, transforming data valorisation towards under age obesity prevention and future research. Moreover, the Bio-Streams framework for data handling, provides robust and transparent methodologies for operational procedures (data infrastructures), analysis and reporting (via meta-reviews and AI-based Apps/components, evaluated via 12 multi-site pilots (7 clinical and 5 schools)), citizen awareness and lifestyle alteration, delivering obesity prevention guidelines, knowledge generation while fostering considerable opportunities for regional and national health authorities/policymakers.