AIDA brings a transformational innovation to the analysis of heliophysics data in four steps. First, AIDA will develop a new open source software called AIDApp written in Python (a free language) and capable of collecting, combining and correlating data from different space missions. AIDApp wants to replace mission-specific tools written for costly languages (such as IDL) that exclude many scientists, students and amateur space enthusiasts from exploring the data, with a much-needed single platform where methods are shared and continuously improved by the whole community. Second, AIDA will introduce modern data assimilation, statistical methods and machine learning (ML) to heliophysics data processing. Unlike traditional methods based on human expertise, these methods rely on statistics and information theory to extract features that are hidden in the data. Third, AIDA will combine real data from space missions with synthetic data from simulations developing a virtual satellite component for AIDApp. This feature will be demonstrated in the comparison with existing mission data and in the planning of new missions (e.g. ESA’s THOR). Fourth, AIDA will deploy in AIDApp methods of Artificial Intelligence (AI) to analyse data flows from heliophysics missions. This task requires bridging together competences in computer science and in heliophysics and pushes well beyond the current state of the art in space data analysis, connecting space researchers with AI, one of the fastest growing trends in modern science and industrial development. AIDA will use the new AIDApp in selecting key heliophysics problems to produce a database (AIDAdb) of new high-level data products that include catalogs of features and events detected by ML and AI algorithms. Moreover, many of the AI methods developed in AIDA will themselves represent higher-level data products, for instance in the form of trained neural networks that can be stored and reused as a database of coefficients.

With the increase of the density of people in urban areas, modern cities experience significant needs related to planning, maintenance and administration. As a result, many cities are engaged in massive investment for infrastructure development across many structural elements including water supply, lighting, maintenance, traffic and transportation systems, refuse disposal and all the factors which form a part of the completed city. The public transportation systems, assisting the movement of people in urban areas using group travel technologies such as buses and trains, are continuously evolving in terms of areas coverage, comfort and technology. Such systems can be exploited by the cities in order to serve both public and benefits including: • Maintenance of infrastructure such as lighting, road deteriorations etc. • Inspection of points of interests such as parking spaces, garbage collection points etc. • Provision of services to the private sector such as inspection of advertisement points etc. The main objective of the GHOST project is to design, develop and validate at an operational environment a GALILEO-based intelligent system for vehicles in order to take advantage of the public transportation fleet routes, towards enabling development of new cross-functional applications for infrastructures maintenance, street parking and garbage management in smarter cities environment. The GHOST intelligent system will be validated at an operational environment, by demonstrating and experimenting on three (3) use cases of the GHOST applications including: • Reporting of street lighting anomalies or road deteriorations (ex: pothole). • Detection of double parking or occupied parking reserved for disabled drivers by unauthorized vehicles. • Monitoring of public garbage completion level.

The TeamPlay project aims to develop new, formally-motivated, techniques that will allow execution time, energy usage, security, and other important non-functional properties of parallel software to be treated effectively, and as first- class citizens. We will build this into a toolbox for developing highly parallel software for low-energy systems, as required by the internet of things, cyber-physical systems etc. The TeamPlay approach will allow programs to reflect directly on their own time, energy consumption, security, etc., as well as enabling the developer to reason about both the functional and the non-functional properties of their software at the source code level. Our success will ensure significant progress on a pressing problem of major industrial importance: how to effectively manage energy consumption for parallel systems while maintaining the right balance with other important software metrics, including time, security etc. The project brings together leading industrial and academic experts in paral- lelism, energy modeling/transparency, worst-case execution time analysis, non-functional property analysis, compi- lation, security, and task coordination. Results will be evaluated using industrial use cases taken from the computer vision, satellites, flying drones, medical and cybersecurity domains.

Medtech products belongs to a huge expanding market, in which Europe hosts some of the biggest global player, accounting for 30% of the world market and for more than 575,000 people employed by nearly 25,000 medical technology companies – 95% of which are SMEs. Symbionica project focuses on the manufacturing of personalized bionics, smart endoprosthetics and exo-prosthetics that require geometric and functional customization. The Symbionica concept integrates an innovative machine performing deposition of advanced materials and subtractive processes along with a supply chain distributed co-engineering platform for advanced design and full personalization involving all relevant stakeholders, design and engineering of the products and through-life services. Symbionica manufacturing solution is conceived as a multi-material AM machine for material deposition and ablation, flexible and reconfigurable in the working cube, the material processing, the technology and the manufacturing strategy, with an advanced closed loop control methodology for product and process quality monitoring. This way Symbionica products are manufactured in one processing step, complex in shape, 3D structured and joint free. The Cooperative Design Platform will guarantee seamless data integration, reverse engineering from patient and parametric design to couple patient specific parts to standard ones. At the end, a Bionic Through-life Sensing System will support the patient to approach and gradually become comfortable with the prosthesis by assisting him with an exercise plan, a physiology monitoring platform and an on-line prosthesis data collection. The Symbionica consortium involves 3 LE, 6 SME and 2 RTD partners from 5 EU countries embracing the Medtech value chain from the patient and prosthetist to the technology providers of the mechatronics modules, IT solutions and control platforms.