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PUBLISHED November 2022 AUTHORS: Dr. Azad M. Madni, Dr. Dan Erwin UNIVERSITY OF SOUTHERN CALIFORNIA In this study, led by Principal Investigator Dr. Azad M. Madni of the University of Southern California, a risk-based validation approach was developed and applied to the acquisition of an Unmanned Aerial Vehicle (UAV) to detect forest fires. The concept of risk was defined within the context of system acquisition and defined an initial validation metamodel. The system comprises a UAV with a GPS and two cameras that can send photos to a processing facility. The validation method was based on the detection of hot spots and smoke. The central idea was to build a tree to help evaluate what-if analyses, look for overlaps and gaps, and help prioritize validation demonstrations.

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