OrbitChain: Orchestrating In-orbit Real-time Analytics of Earth Observation Data
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Abstract (arXiv)
Earth observation analytics have the potential to transform many sectors. However, due to limited ground connections, it currently takes hours to days to download and analyze Earth observation data, diminishing the value of data for time-sensitive applications like disaster monitoring or search-and-rescue. To enable real-time analytics, we propose OrbitChain, an in-orbit multi-satellite Earth analytics framework. OrbitChain uses a pipelined design to decompose workflows into analytics functions, and orchestrates constellation-wide resources to finish real-time analytics tasks. It provides timely insights to Earth sensing applications and enables advanced workflows like in-orbit tip-and-cue. Hardware-in-the-loop experiments show that OrbitChain can deliver analytics results in minutes, supports up to 60% more analytics workload than existing frameworks, and reduces inter-satellite communication overhead by up to 45%.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 56 references that are in the map. First posted on arXiv 18 Aug 2025.
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11 of 56 references.
References · 11
- 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,442
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- 2024Earth+: on-board satellite imagery compression leveraging historical earth observationscited by 6
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- 2025B2LoRa: Boosting LoRa Transmission for Satellite-IoT Systems with Blind Coherent Combiningcited by 1
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