By Value-Aware AI we mean AI that includes a component performing the same function as human moral consciousness, namely the capacity to acquire and maintain a value system, use this value system to decide whether certain actions are morally acceptable and be aware of the value systems of its users so as to understand the intent and motivation of their actions and to properly and correctly engage with them. The VALAWAI project will develop a toolbox to build Value-Aware AI resting on two pillars both grounded in science: An architecture for consciousness inspired by the Global Neuronal Workspace model developed on the basis of neurophysiological evidence and psychological data, and a foundational framework for moral decision-making based on psychology, social cognition and social brain science. The project will demonstrate the utility of Value-Aware AI in three application areas for which a moral dimension urgently needs to be included: (i) social media, where we see many negative side effects such as disinformation, polarisation, and the instigation of asocial and immoral behavior, (ii) social robots, which are designed to be helpful or influence human behavior in positive ways but potentially enable manipulation, deceit and harmful behavior, and (iii) medical protocols, where VALAWAI tries to ensure medical decision making is value aligned. The project contributes to the general goal of making EU-based AI more competitive by being more reliable, robust, ethically-guided, explainable and hence trustworthy. It does not make new proposals for guidelines and regulations (for which there is already considerable effort) but advances the state of the art in core AI technology so that ethics is embedded inside applications making them grounded in universal, European and personal values.

All over Europe, young farmers are starting small market farms. These farms can be found both in rural, peri-urban and urban areas. They grow a large variety of crops (up to 100 different varieties of vegetables per year) on small surfaces (0.01 to 5 ha) using organic farming practices. These farms have proven to be highly productive, sustainable and economically viable. But, a lot of work is done manually, resulting in physically challenging work conditions. ROMI will develop an open and lightweight robotics platform for these microfarms. We will assist these farms in weed reduction and crop monitoring. This will reduce manual labour and increase the productivity. Thanks to ROMI’s weeding robot, farmers will save 25% of their time. This land robot will also acquire detailed information on sample plants and will be coupled with a drone that acquires more global information at crop level. Together, they will produce an integrated, multi-scale picture of the crop development that will help the farmer monitor the crops to increase efficient harvesting. For this, ROMI will have to adapt and extend state-of-the-art land-based and air-borne monitoring tools to handle small fields with complex layouts and mixed crops. To achieve this, we will: (i) develop and bring to the market an affordable, multi-purpose, land-based robot, (ii) develop a weeding app for this robot that is adapted for organic microfarms, (iii) apply advanced 3D plant analysis and modelling techniques to in-field data acquisition, (iv) integrate these analysis techniques in the robot for detailed plant monitoring, (iv) integrate these techniques also in the aerial drone N-E-R-O for multi-scale crop monitoring, (v) extend the robot with novel, adaptive learning techniques to improve sensorimotor control of the plant monitoring app, and (vii) test the effectiveness of our solution in real-world field conditions. A spin-off will be created to bring the robot and the drone to the market of micro-farms.

The overarching goal of BEYOND5 is to build a completely European supply chain for Radio-Frequency Electronics enabling new RF domains for sensing, communication, 5G radio infrastructure and beyond. BEYOND5 is first and foremost a technology project gathering most significant European actors covering the entire value chain from materials, semiconductor technologies, designs and components up to the systems. BEYOND5 will drive industrial roadmaps in More than Moore (MtM) in adding connectivity features on existing CMOS Technology. The ambition is to accomplish sustainable Radio Frequency SOI platforms to cover the frequency range from 0.7GHz to more than 100GHz, and to demonstrate the technical advantage of SOI, which allows combining large scale integration, low power consumption, cost competitiveness and higher reliability; thus, resulting in high volume production of trusted components with low environmental impact in Europe. This objective will be achieved in a “Time to Market” approach using the 3 major work streams: 1. Technology enhancement in three European industrial pilot lines: • 300mm RF SOI substrates pilot line in Soitec, supported by the “Substrate Innovation Center” in CEA LETI to prepare future generations. • RF-SOI 65nm pilot line for 5G FEM in ST addressing both sub-6GHz and 28GHz domains. • 22FDX pilot line addressing Digital Signal Processing of radio module and RF reliability, in GF 2. European RF design ecosystem strengthening, based on a large fabless community using FD-SOI and RF-SOI platforms 3. Six Leading edge systems aggregating the value chain to demonstrate added-value of the technology at the user level: • NB IoT for Smart Asset Tracking, • Contactless USB for high-data rate communication, • V2X for autonomous connected trucks, • 5G Low Power Digital Beamforming Base Station for Indoor dense spaces, • Automotive MIMO Radar with embedded AI, • Car Interior Radar for passenger monitoring.

Europe gave birth to the industrial revolution about two centuries ago thanks to the convergence of a series of factors that allowed technology to be closer to society, while creating economic benefits to regional and national economies. With the globalisation, European cities lost a large volume of manufacturing capacity and transitioned to a knowledge economy. The result: a decrease in manufacturing jobs, the lack appreciation for these jobs, and neglected industrial areas subject to decay. Decay of industrial heritage has a major imprint on European city's identities, but also is a source of opportunity. The result, industrial areas with high historical value for Europe being abandoned or exploited by extractive economic activities, with no connection to local knowledge, and with no generation of value at the local level. CENTRINNO aims to develop and demonstrate strategies, approaches and solutions for regeneration of industrial historic sites and areas as creative production and manufacturing hubs, that 1) hold true to the ecological challenges of our time, 2) boost a diverse, inclusive and innovative urban economy, and 3) and use heritage as a catalizer for innovation and social inclusion. We give centre stage to craftsmen, vocationally trained professionals, entrepreneurs, makers, SME’s, Fab Labs, Food Labs and Makerpaces to become key players in the cities supply of local goods and support them to take on a fundamental role in our future cities, thus opposing disengagement and stagnation of local economies. Through a holistic method combining the Fab City Global Initiative approach to productive cities with Emotion Networking, life cycle assessment and spatially-specific material flow analyses, we bring to the fore both complex, layered histories of these sites as well as the cities available resources in terms of urban landscape, materials, current day skills and practice and human capital.

Music Information Processing (also known as Music Information Research; MIR) involves the use of information processing methodologies to understand and model music, and to develop products and services for creation, distribution and interaction with music and music-related information. MIR has reached a state of maturity where there are standard methods for most music information processing tasks, but as these have been developed and tested on small datasets, the methods tend to be neither robust to different musical styles or use contexts, nor scalable to industrial scale datasets. To address this need, and to train a new generation of researchers who are aware of, and can tackle, these challenges, we bring together leading MIR groups and a wide range of industrial and cultural stakeholders to create a multidisciplinary, transnational and cross-sectoral European Training Network for MIR researchers, in order to contribute to Europe's leading role in this field of scientific innovation, and accelerate the impact of innovation on European products and industry. The researchers will develop breadth in the fields that make up MIR and in transferable skills, whilst gaining deep knowledge and skills in their own area of speciality. They will learn to perform collaborative research, and to think entrepreneurially and exploit their research in new ways that benefit European industry and society. The proposed work is structured along three research frontiers identified as requiring intensive attention and integration (data-driven, knowledge-driven, and user-driven approaches), and will be guided by and grounded in real application needs by a unique set of industrial and cultural stakeholders in the consortium, which range from consumer electronics companies and big players in media entertainment to innovative SMEs, cultural institutions, and even a famous opera house, thus encompassing a very wide spectrum of the digital music world.