AI-Driven Aerial Corrosion Detection: Capabilities, Limitations, and Future Directions

Corrosion poses a persistent threat to infrastructure integrity across critical industries. Traditional inspection methods often suffer from safety concerns, accessibility limitations, and human subjectivity. While drone-enabled corrosion detection systems offer promising solutions by leveraging advanced sensing technologies and AI, existing review studies often lack a comprehensive analysis of both the technological advancements and the practical challenges hindering widespread adoption. This paper addresses this gap by providing a comprehensive review of AI-driven aerial corrosion detection, critically evaluating current capabilities, identifying key limitations, and proposing future research directions. We aim to articulate the research problem by highlighting the deficiencies in current review approaches and emphasizing the specific gaps our study aims to fill, particularly concerning the convergence of AI, digital twin frameworks, and multi-sensor fusion strategies for enhanced reliability and scalability of autonomous corrosion assessment systems.