OrbitChain: Orchestrating In-orbit Real-time Analytics of Earth Observation Data
Zhouyu Li, Zhijin Yang, Huayue Gu, Xiaojian Wang, Yuchen Liu, Ruozhou Yu

TL;DR
OrbitChain is a novel in-orbit multi-satellite framework that enables real-time Earth observation data analytics, significantly reducing latency and increasing workload capacity compared to existing methods.
Contribution
It introduces a pipelined, orchestrated in-orbit analytics system that improves real-time processing and resource utilization for Earth observation satellites.
Findings
Delivers analytics results in minutes
Supports 60% more workload than existing frameworks
Reduces inter-satellite communication by 45%
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAstronomical Observations and Instrumentation · Big Data Technologies and Applications · Inertial Sensor and Navigation
