Publication | Closed Access
Towards the Use of Artificial Intelligence on the Edge in Space Systems: Challenges and Opportunities
236
Citations
36
References
2020
Year
Artificial IntelligenceSpace DataEngineeringOrbital PlatformsComputer ArchitectureIntelligent SystemsSpace SystemSpace RoboticsData ScienceSpace VehiclesSpace SystemsSystems EngineeringSatellite ImagingEdge IntelligenceComputer EngineeringComputer ScienceSmall SatelliteAerospace EngineeringEdge ComputingSpace Mission DesignCloud ComputingRemote SensingSpace ArchitectureDownlink BandwidthEdge Artificial Intelligence
The market for remote sensing space‑based applications is fundamentally limited by up‑ and downlink bandwidth and onboard compute capability for space data handling systems. This article details how the compute capability on these platforms can be drastically increased by leveraging emerging commercial off‑the‑shelf system‑on‑chip technologies. The authors leverage these COTS SoCs to boost onboard compute, report initial radiation tolerance and power/performance results, and outline a path toward low Earth orbit trials and a full life‑cycle for space‑based AI classifiers. The resulting orders‑of‑magnitude increase in processing power enables data consumption at source, reduces downlink bandwidth usage, and could revolutionize Earth observation and other remote sensing applications by dramatically cutting the time and cost to deploy new value‑added services.
The market for remote sensing space-based applications is fundamentally limited by up- and downlink bandwidth and onboard compute capability for space data handling systems. This article details how the compute capability on these platforms can be drastically increased by leveraging emerging commercial off-the-shelf (COTS) system-on-chip (SoC) technologies. The orders of magnitude increase in processing power can then be applied to consuming data at source rather than on the ground allowing the deployment of value-added applications in space, which consume a tiny fraction of the downlink bandwidth that would be otherwise required. The proposed solution has the potential to revolutionize Earth observation (EO) and other remote sensing applications, reducing the time and cost to deploy new added value services to space by a great extent compared with the state of the art. This article also reports the first results in radiation tolerance and power/performance of these COTS SoCs for space-based applications and maps the trajectory toward low Earth orbit trials and the complete life-cycle for space-based artificial intelligence classifiers on orbital platforms and spacecraft.
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