Safe4RAIL-3 and its activities will be based on the development of three technological pillars aimed at advancing the maturity of the technologies and devices for the next generation for Train Control and Monitoring System (TCMS), in order to pass from prototypes level to TRL 6/7: (1) Development of the Drive-by-Data (DbD) devices in the train network, i.e. Ethernet Train Backbone Nodes, Car Switches and End Devices, using Time-Sensitive Network technology for adding determinism to TCMS communications.(2) Development of high TRL wireless devices and antennas that are suitable for Wireless TCMS (WLTB and WLCN domains), along with analysis of antenna installation based on ray-tracing simulations and on-site validations to identify the most optimal antenna locations and radiation patterns in the different wireless TCMS domains (3) Integration of a Heating, Ventilation and Air Conditioning functionality on top of a Functional Distribution Framework platform and a DbD communication layer, taking advantage of the expertise obtained from automotive industry specialized on AUTOSAR. Safety and Security assessments for these technological developments will be analyzed and studied based on the upcoming standardization. All these technological developments will be further validated in two real demonstrators that will be set up by the Shift2Rail CFM project and will also contribute to standardization. These results will increase the flexibility and reliability of the TCMS communications, reduce development and maintenance costs, and achieve novel train functionalities, paying special attention to manufacturer interoperability and the availability of multiple sources. The consortium consists of 10 partners with specific industrial profiles and expertise in key technologies from 7 European countries, including 8 industrial partners, 2 academic partners. Such an industry-oriented consortium has been considered crucial to bring the selected technologies to higher TRL up to TRL-7.

Recent years have seen the widespread diffusion of low-cost computational systems, triggering the transition towards even further decentralization towards the Edge of autonomic intelligence. While in the consumer domain this transformation is happening very fast, industrial applications are inevitably more conservative and require solid methodological and technological grounds to guarantee this transition to be dependable. 1-SWARM project focuses on the design-operations for CPSoS with the specific focus on industrial sector of large-scale distribution and logistics. The project aims at achieving industrially acceptable level of robustness of CPSoS whose operation emerges as “Swarm Intelligence”. 1-SWARM’s solution will span across different steps of the value chain, connecting intelligence through the digital domain to maximize their effectiveness and reliability. The objective is to provide a methodological and technological framework, modular and re-usable (“Swarm Intelligence DevOps Framework”), for the engineering of the three major aspects of CPSoS: i) The HW/SW runtime platform that sustains their operations; ii) The distributed and orchestrated Intelligence that guarantees their autonomic behavior; iii) The extension of their “existence” into the cyber-domain for a full life-cycle approach. Key to the exploitability of 1-SWARM’s result is the demonstration of its potentialities for 4 different application scenarios, whose requirements come from cross-domain use-cases, whose variability allows extensive validation of the project technologies: 1) Manufacturing CPSoS for food packaging; 2) Logistics CPSoS for reconfigurable material handling; 3) Fleets of intelligent AGVs in complex dynamic environment; 4) Aerial drones flock for extensive monitoring of retails shops. Strong of its open and standard-based approach, 1-SWARM will create an international collaborative framework for the CPSoS domain, supporting extensively relevant standardization activities.

The project's main objective is to develop a highly innovative, secure-by-design framework that fully exploits the MaaS paradigm. This framework will offer secure data exchange between companies and cutting-edge tools to enhance production efficiency and sustainability. The MEDUSA framework will establish a seamless connection between existing marketplaces, facilitating optimized production by leveraging users' machinery and shared resources from other manufacturers. All resources will be treated as part of a distributed Cyber-Physical System of Systems (CPSoS), maximizing production. The implementation of an automation layer will enable the exchange of real-time production data and asset monitoring, allowing for the tracing and optimization of the product life cycle. The framework will also support the implementation of a DPP and provide AI-based tools for manufacturers to support decision-making for production planning, remanufacturing, and machine reconfiguration, always being energy-aware.

WASABI aims at providing SMEs with the tools and knowledge to improve workers capacities and performance, providing advanced user interfaces for continuous augmented hybrid-decision-making. Such interfaces assist employees in interacting with complex software, effectively reducing its skill floor. In consequence, humans will find using software easier and be more open to applying it effectively at work. WASABI’s advanced interfaces will cover, for instance, situation analysis, intervention identification, action planning and execution, and impact monitoring and mitigation. One of the key technologies in WASABI’s solution portfolio is the digital intelligent assistant (DIA) - an anthropomorphic, task-oriented AI with a conversational interface. A network of DIHs that will help boosting impact by guiding SMEs in this new path will be created and integrated within other existing DIH networks. Our customized, federated, white-label shop will include such DIAs and skill-packages to help organizations reach their sustainability goals. Blue-collar and white-collar workers will be capable of using it for hands-free or eyes-free computer-interaction, AI-based advice and guidance, and augmented analytics.

Smart factories are characterised by smart processes, smart machines, smart tools and smart products as well as smart logistics operations. These generate large amounts of data, which can be used for analysis and fault prevention, as well as the optimisation of the quality of manufacturing processes and products. DAT4.ZERO is a Digitally-enhanced Quality Management System (DQM) that gathers and organizes data from a Distributed Multi-sensor Network, which, when combined with a DQM Toolkit and Modeling and Simulation Layer, and further integrated with existing Cyber-Physical Systems (CPS), offers adequate levels of data accuracy and precision for effective decision-support and problem-solving – utilizing smart, dynamic feedback and feed-forward mechanisms to contribute towards the achievement of Zero Defect Manufacturing (ZDM) in smart factories and their ecosystems. The aim is to Integrate smart, cost-effective sensors and actuators for process simulation, monitoring and control; develop real-time data validation and integrity strategies within actual production lines; demonstrate innovative data management strategies as an integrated approach to ZDM; & develop strategies for rapid line qualification and reconfiguration. Deployed in 5 distinct industrial pilot lines we address the following primary objective: Develop and demonstrate an innovative DQM system and deployment strategy for supporting European manufacturing industry in realizing ZDM in highly dynamic, high-value, high-mix, low-volume production contexts, by effective selection and integration of sensors and actuators for process monitoring and control, a DQM platform with an architecture that provides reliable and secure knowledge extraction to ensure integrity of data, & strategies for advanced realtime data analysis and modeling in multiple domains and sectors that will increase quality, reduce ramp-up times and decrease time-to-market.