Reinventing Satellite Communication: Domino’s Quest for Scalability and Cost-Efficiency

Philippe Pavero, an engineer at Airbus Defence and Space, is part of the Mission Algorithms for Earth Observation team, focusing on optimizing satellite communications in the groundbreaking Domino-E project. He shares insights into how Domino’s scalable, cloud-based approach revolutionizes Earth observation and satellite communications, allowing more efficient data management and cost reduction. By linking multiple satellite constellations and ground stations, Domino-E enhances reactivity, making it a game-changer for space communication systems.

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One Domino at a Time: Daniel Novak (ADS) on the Future of the Earth Observation Architecture

The Domino architecture is a groundbreaking approach in Earth observation, focused on standardizing ground segments for satellite missions. By introducing modular, autonomous components called “Dominos,” it simplifies system integration, reduces development time, and lowers costs. This innovative framework allows different companies, including SMEs, to specialize in creating specific, standardized modules that seamlessly fit together. Similar to how the USB standard transformed IT, Domino enables greater collaboration across the space industry, fostering efficiency and innovation in Earth observation projects.

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Fostering Collaboration in Earth Observation: Introducing the Domino Architecture

Domino-E contributes to the Domino architecture, creating a novel way of cooperation in European Earth observation.   The Domino framework presents a groundbreaking approach to Earth observation (EO) by fostering a collaborative environment where industry and science work together throughout the entire development lifecycle, from initial concept to final validation of modular EO building blocks.…

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Domino-E at the 23rd International Conference on Autonomous Agents and Multiagent System

ONERA’s Gauthier Picard presented his work at the AAMAS’24 in Auckland, New Zealand. Agent-based and multi-agent systems (MAS) in space offer a promising approach for modeling and solving distributed, complex and dynamic problems. Sample applications include multiple spacecraft operations and maintenance, onboard-ground coordination, mission simulation, multi-mission operation, autonomous navigation, and collective robotics. The Domino-E project…

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Applying Earth Observation: Energy Poverty

The 3,5-year project EnergyMeasures is wrapping up in Brussels. The EU-funded project was launched to identify households affected by energy poverty, to develop strategies that would  support them in adopting less energy-intensive behaviours, and to provide decision-makers of all levels with evidence-based policy recommendations to tackle energy poverty. As the project winds down, one of the key conclusions was to…

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Along the river: the stream of Earth observation

Rivers are divided into upstream, midstream, and downstream. This tripartite division also helps to understand the earth observation processing chain. Rivers are traditionally divided into three sections along their course based on the gradient between their source and delta: upstream, midstream and downstream. This division is often used metaphorically to describe industrial value chains.  The…

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Machine learning in Domino-E use cases

What exactly is machine learning (ML) and  how does Domino-E make use of it in planning, resource allocation and human-computer interactions? In what ways does it benefit users? In this article we focus on answering these and other questions regarding machine learning in Earth Observation.  Earth Observation (EO) produces a vast quantity of often unstructured data.…

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Climate change tracking from space: From mono to multi-mission design 

Photo by ROMAN ODINTSOV: https://www.pexels.com/photo/aerial-shot-of-heaps-of-icy-snow-on-a-glacier-and-turquoise-melted-ice-6979890/

Earth observation satellites provide valuable information on greenhouse gas emissions, deforestation, melting glaciers, and other indicators of climate change. The move from mono- to multi-mission design allows better data access.

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