Lanre Daniyan
Papers
2
Total Citations
17
H-Index
2
About
Lanre Daniyan is a forward-thinking researcher at the intersection of robotics, non-destructive testing, and intelligent industrial systems. His primary research areas center on developing autonomous inspection technologies and integrating artificial intelligence with predictive maintenance to enhance the reliability of critical infrastructure. Daniyan’s most influential work, "Development of an inline inspection robot for the detection of pipeline defects" (2021, 15 citations), introduces a specialized robot designed for non-destructive testing of pipelines. This innovation directly addresses the costly and hazardous problem of undetected cracks and corrosion, aiming to reduce product loss and improve operational safety. By advancing robotic solutions for real-world asset monitoring, he provides a tangible method for moving beyond reactive repairs. More recently, his comprehensive review on "Artificial intelligence and robotics in predictive maintenance" (2026) synthesizes how AI and robotics are shifting industrial maintenance from scheduled, reactive models to proactive, data-driven strategies. Through his work, Daniyan demonstrates a clear commitment to bridging the gap between theoretical AI frameworks and practical robotic applications, making significant contributions to safer, more efficient industrial operations.
Research Focus
Key Achievements
Top Papers
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- 2