Manufacturers of automated systems and the manufacturers of the components used in these systems have been allocating an enormous amount of time and effort in the past years developing and conducting research on automated systems. The effort spent has resulted in the availability of prototypes demonstrating new capabilities as well as the introduction of such systems to the market within different domains. Manufacturers of these systems need to make sure that the systems function in the intended way and according to specifications which is not a trivial task as system complexity rises dramatically the more integrated and interconnected these systems become with the addition of automated functionality and features to them. With rising complexity, unknown emerging properties of the system may come to the surface making it necessary to conduct thorough verification and validation (V&V) of these systems. VALU3S aims to design, implement and evaluate state-of-the-art V&V methods and tools in order to reduce the time and cost needed to verify and validate automated systems with respect to safety, cybersecurity and privacy (SCP) requirements. This will ensure that European manufacturers of automated systems remain competitive and that they remain world leaders. To this end, a multi-domain framework is designed and evaluated with the aim to create a clear structure around the components and elements needed to conduct V&V process through identification and classification of evaluation methods, tools, environments and concepts that are needed to verify and validate automated systems with respect to SCP requirements. The implemented V&V methods as well as improved process workflows and tools will also be evaluated in the project using a comprehensive set of demonstrators built from 13 use cases with specific SCP requirements from 6 domains of automotive, industrial robotics, agriculture, Aerospace, railway and health.

Existing measurements of equipment and building energy use paint a bleak image: real-life energy consumption often exceeds design predictions by more than 100%. As a result, reducing the gap between designed and measured energy use has become central in current efforts to increase energy efficiency. After the successful introduction of building energy performance certificates, the market is now ready for an assessment of real-life energy use that includes all energy consuming equipment in a given building. With this evolution comes the possibility of optimizing energy performance of the whole building and its energy consuming equipment. The SATO project tackles this challenge by (1) Creating a new energy self-assessment and optimization SATO platform that integrates all energy consuming equipment and devices in the building; (2) Developing and integrating into the SATO platform a self-assessment framework (SAF) that uses data analysis and machine learning to report energy performance, building behaviour, occupancy and equipment faults. This framework is aligned with the structure of the smart readiness indicator (SRI); (3) Developing a BIM-based interface for aggregated and disaggregated analysis and visualization of the assessments in the various applicable scales and defining locations and specifications of energy consuming equipment, sensors and actuators into a BIM building model; (4) Develop and demonstrate energy management services that use the SATO platform and show how the self-assessment and optimization contributes to lower energy consumption, increased energy flexibility, efficiency and user satisfaction.

The number of available software applications in the form of web services, mobile apps, etc., is dramatically increasing over the years. This software exploits data collected through various sensors, and online data sources. Its users can access it through a variety of devices, mostly based on mobile technology. Software providers can hardly predict the acceptance of the applications they deliver. The great diversity in execution contexts and user preferences makes it difficult to personalize the software to fit all users’ needs. The complexity of those systems and the data involved turn out to be a solution to the problem and offer new opportunities for software engineers The SUPERSEDE project proposes a feedback-driven approach for software life cycle management, with the ultimate purpose of improving users’ quality of experience. Decisions on software evolution and runtime adaptation will be made upon analysis of end-user feedback and large amount of data monitored from the context. An integrated platform will articulate the methods and tools produced in the project. The project will provide advancements in several research areas however, the major contribution will be in integrating methods and tools from the mentioned areas, thus providing a new solution framework for software evolution and adaptation for data-intensive applications Three use cases have been identified to provide a solution, which is based on the needs of different companies. They are representative for different data-intensive application domains (i.e. energy consumption, sport event webcasting). This diversity also allows a validation of the methods and tools produced to ultimately provide evidence of potential for productivity gains. CONSORTIUM: 8 partners with large scientific, dissemination and exploitation expertise on the topics of the project. Balanced consortium from different perspectives: geographical (5 countries) and profile (4 academic partners + 4 companies, 2 large and 2 SMEs).