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The core objective of MBSE-IT was to provide a digital link between ground segment systems and the infrastructure on which the software is deployed and it was implemented by the definition of a physical deployment model for the system as a dedicated viewpoint on the overall system model for the ground segment.

AbC is a compact on-board algorithm, initially intended for CubeSats, to measure the absolute direction of a distant beacon with optimised accuracy. The AbC environment anticipates a ground pipeline that has been used with OPS-SAT images to diagnose the ADCS. It has been shown that a ground-truth assessment of the satellite's orientation can be made which, with sufficient data, could allow precise re-alignment of multiple sensors. The ESA contract funded the implementation of the on-board algorithm in C++ and its pipeline in Python.

An interplanetary probe must decelerate from a hyperbolic interplanetory trajectory to an orbital trajectory when it arrives at its destination. Currently, this maneuvre is achieved using chemical propulsion, which means that propellant makes up a significant fraction of the vehicle mass. Aerocapture is an alternative concept that instead uses aerodynamic drag from the athmosphere of the planet to decelerate the arriving spacecraft.

The architecture of an SPS system requires that the SPS maintain constant visibility to both the Sun and the ground station. This immediately implies a so-called Geosynchronous Equatorial Orbit (GEO), which is also called a Geostationary Orbit; or a near-GEO Geosynchronous Orbit (GSO). These are substantially the same orbits that are used for existing communications satellites.

Visualisation is the bridge between the quantitative information hidden in the data and the human intuition and understanding; it is a challenge of key importance in the present ?Big Data? era. In all three segments of the Space Safety Programme (S2P) large amounts of data are produced daily. Adequate visualisation can lead to more effective analysis of diverse aspects and increase knowledge about the unfolding of different phenomena. For example, the main current means of visualisation of Space Weather phenomena used by scientists and operators are 2D and in few cases 3D graphs.

The ENHANCE (Enabling Harbor to Harbor Autonomous Situational Awareness in Sea Ice Conditions) project is aimed to study How to improve the autonomous navigation and situational awareness in the maritime domain by utilising ML and AI concepts. For this end, we utilise both traditional RGB cameras as well as IR cameras to obtain as diverse as possible data set of sea-ice conditions to train a ML model that can identify an ice tracks and objects, such as buoys, that can help in navigation.

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