A Generic On-Board AI Processing Chain for Earth Observation: From Application Development to Embedded Deployment and Mission-Level Orchestration
Extracting information on board with artificial intelligence (AI) turns the satellite into a data-reduction stage that downlinks compact products, such as masks or detections, instead of full scenes; deploying it in a mission, however, involves the whole processing chain and not only the neural network.
ProofPaper ↗
Key points
- Earth observation satellites acquire more data than they can downlink.
- The chain is characterized end to end, from the standalone execution on the target to its execution under orchestration with parallel workflows on a representative test bench.
- Beyond AI inference on individual tiles, this approach aims at increasing the maturity of on-board AI deployment by addressing a complete processing chain, from the acquired scene to the mission-level execution.
Sources (1)
- [1]A Generic On-Board AI Processing Chain for Earth Observation: From Application Development to Embedded Deployment and Mission-Level OrchestrationarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 01:08 PM
Extracting information on board with artificial intelligence (AI) turns the satellite into a data-reduction stage that downlinks compact products, such as masks or detections, instead of full scenes; deploying it in a mission, however, involves the whole processing chain and not only the neural network.
Earth observation satellites acquire more data than they can downlink.
Extractive summary: sentences quoted from the sources.
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