Modern satellite complexity is increasing, thus requiring bespoke and expensive on-board solutions to provide a Failure Detection, Isolation and Recovery (FDIR) function. Although FDIR is vital in ensuring the safety, autonomy, and availability of satellite systems in flight, there is a clear need in the space industry for a more adaptable, scalable, and cost-effective solution. This paper explores the current state of the art for machine learning error detection and prognostic algorithms

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... ed by both the space sector and the commercial sector. Although work has previously been done in the commercial sector on error detection and prognostics, most commercial applications are not nearly as limited by the power, mass, and radiation tolerance constraints imposed by operation in a space environment. Therefore, this paper also discusses several Commercial Off-The-Shelf (COTS) multi-core micro-processors-smallfootprint boards that will be explored as possible testbeds for future integration into a satellite in-orbit demonstrator.