The STARS project paves the way for the future EGNSS deployment in safety relevant railway applications. By evolving the highly developed and deployed ERTMS standard through the implementation of the satellite positioning functionality, it will be possible to reduce the cost of the future railway signalling systems, especially for lines with lower traffic density. The project deals with three main topics: 1) The elaboration of reference data and characterisation of the railway environment through a measurement campaign; 2) The assessment of the EGNSS performances achievable in the railway environment with the determination of the applicable requirements for the positioning system as well as the necessary evolutions of EGNSS services and ERTMS/ETCS functions and 3) Quantification of the economic benefits and specifying the possible implementation roadmap when applying the EGNSS on railways. The project is strongly linked with other initiatives and actions on the same topic in Europe. In order to feed directly into the standardization work of ERTMS, the project partners will cooperate closely with UNISIG. Moreover, the project will actively interact with NGTC (EU funded FP7) and the results will be directly implemented by SHIFT2RAIL, providing the practical demonstrators for different categories of railway tracks. The approach developed in STARS is also taking the profit of the strong know-how inherited from civil aviation, making this project as completely integrated and consistent in overall activities in Europe and worldwide, leading to the effective deployment of the satellite technologies in advanced railway signalling systems.

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