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Blockchain ecosystem for an autonomous consensus mechanism of federated satellite networks – Space DAO

In applications such as space traffic and disaster response management, there are growing public and private capabilities. Multiple different stakeholders can detect and identify events (space collision predictions, natural disaster definitions). Augmentation of events definitions lead to confusion for local authorities, operators or any users of these information for costly decisions. This project, Space DAO, sets the base infrastructure to agree on consensus mechanisms to reduce confusion and augment trust in key decision making information.

Germany

EISI_I-2022-00372

parametry.ai
A Distributed Ledger Approach to MBSE

Main achievement: Development of the first blockchain ecosystem for space system engineering, as a global configuration tool that can model the business logic of concurrent design. Addressing the MBSE challenges of  controlling data exchange and traceability across system development and operations lifecycle.

Results: Two use cases have been successfully implemented

UK

20-D-S-TEC-04-b

UNIVERSITY OF STRATHCLYDE
MBSE enhanced by Semantic DataLake integration and Machine Learning

The Integrated MBSE Analytics Platform (IMAP) has been developed in the course of the OSIP [OSIP] MBSE campaign’s MBSE2DataLake project. It demonstrates how MBSE data can be downstreamed from early phases and integrated with Telemetry data or system operations data. Applying MachineLearning analytics and customized visualization on these sets of integrated data provides seamless analysis capabilities and data browsing experience for the user. The approach leads to linking the former separated domains of System Design and AIT/Operations.

Germany

20-D-T-TEC-04-h

ScopeSET
System Engineering Models meet Knowledge Graphs

Tables and graphs are knowingly used to organise data within a company with different levels of depth and complexity. Knowledge graphs (KGs) are particularly useful because they can cope with data diversity (high-quality complete data and sparse and incomplete data), they have a high degree of scalability and flexibility (the semantic data model can be inter-operational, large, wide and as deep as needed) and, last but not least, they provide reasoning and inference capabilities.

UK

20-D-S-TEC-04-a

UNIVERSITY OF STRATHCLYDE
Artificial Intelligence and drones supporting the detection and mapping of floating aquatic plastic litter (AIDMAP)

Remote detection and mapping of floating marine plastic litter (FMPL) from space needs to operate in synergy with clean up actions. This implicates that an observation system is needed combining high revisit and high spatial resolution. Currently there is no single remote sensing technology with sufficient revisit capabilities and spatial/spectral resolution relevant to FMPL dynamics. Therefore a combination of small drones, satellites and High Altitude Pseudo-Satellite (HAPS) is anticipated to provide the long term sustainable technical solution.

Belgium

20-D-T-TEC-01-n

Vito
Exploiting AI capabilities to facilitate and assist the evaluation process of ideas submitted in the OSIP platform – FEPOSI (Facilitating the Evaluation Process of Open Space Ideas)

The general goal of this project is to operationalize and deepen the findings and conclusions of the initial project “Exploring AI capabilities to support the evaluation process of ideas submitted in the OSIP platform.” which demonstrated that AI techniques and software (COGITO Discover) could be used positively to enhance and ease the evaluation of ideas, by providing some new indicators such as idea novelty (scoring 0-100) based on the notion of similarity between ideas and innovation projects.

Spain

21-D-O-TEC-02

EXPERT SYSTEM IBERIA SLU
Application of MBSE to reverse-engineer OPS-SAT and improve OPS-SAT2

The OPS-SAT MBSE activity had the 3 main objectives:

France

20-D-S-OPS-01-a

Samares Engineering
A Simulator for Marine Litter Observation from Space

“Remote Sensing for Marine Litter - RESMALI” has identified the ideal parameters to study marine litter (ML) from space, including spectral bands with affordable signal-to-noise ratio (SNR) at top-of-atmosphere (TOA) level, in a range of wavelengths from visible to SWIR. To continue this path towards a dedicated mission, performance assessment against simulated real-case scenarios of ML is key. We want to build a simulator to estimate ML signal at TOA from a set of scenarios representing the various applications already targeted by the community (e.g.

France

20-D-T-TEC-01-k

ARGANS LIMITED
End-to-End System Engineering Portal (ESEP)

Space system engineering is a complex activity, spanning multiple phases and involving different stakeholders using a variety of engineering approaches and tools. ESA has been investing in Model-Based System Engineering (MBSE) research for many years, developing different MBSE frameworks and Domain Specific Tools (DSTs). Recently, a broader need has been recognized to focus the MBSE efforts on semantic interoperability and associated model integration.

Germany

20-D-T-TEC-04-d

Spacecube GmbH
Early in the loop MBSE assessment of electronic availability for nano/micro-satellites (ELMASAT)

The main objective of the ELMASAT study was to brint into Capella the means to calculate the availability of a satellite system and provide extra facilities for trade-off analysis. As an example of application, an assesment of SEE detection and mitigation strategies was performed with respect to availability objectives.

France

20-D-T-TEC-04-g

IRT Saint-Exupery

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