Explainable Engineering Monitoring and Low-Altitude Safety
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Keywords

artificial intelligence
materials
uav

Abstract

This review examines explainable monitoring across rotating machinery, metamaterial design, and low-altitude safety through an evidence-centered design lens. The analysis asks how explanations should change an engineering action. It treats the relevant unit as a complete pathway from data or physical observations to representation, model output, human interpretation, and accountable action. The cited literature is synthesized without inventing experiments or unreported performance values. Particular attention is given to salience maps being treated as physical mechanisms. The review argues that credible translation requires explicit evidence boundaries, uncertainty-aware evaluation, author-visible traceability, and a documented route for intervention. The resulting framework supports condition monitoring and autonomous safety while distinguishing component promise from system readiness.

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