Failure prediction and risk mitigation in small uncrewed aerial systems

A Small Uncrewed Aircraft (drone) comprising:

• a plurality of electric motors;
• multiple sensors of different types to generate data relating to operation of the drone;
• and
• one or more data processors including instructions to cause the performance of operations comprising:
• capturing data during operation of the drone from a number of sensors of different types;
• performing analysis on the captured data using one or more Artificial Intelligence/Machine Learning (AI/ML) models that have been trained on data sets including historical drone data and drone system fault data, to predict or identify a potential drone failure mode;
• and
• when a potential failure mode is predicted or identified, providing a course of action for further operation of the drone based on a severity and predicted timing of the potential drone failure mode.

A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to perform operations for operating a Small Uncrewed Aircraft System (SUAS), the operations comprising:

• capturing data during operation of the SUAS from a number of sensors of different types;
• performing analysis on the captured data using one or more Artificial Intelligence/Machine Learning (AI/ML) models that have been trained on data sets including historical SUAS data and SUAS system fault data, to predict or identify a potential SUAS failure mode;
• and
• when a potential failure mode is predicted or identified, providing a course of action for further operation of the SUAS based on a severity and predicted timing of the potential SUAS failure mode.