Oyekola Peter Oluwatosin

Papua New Guinea University of Technology

Papers

Total Citations

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About

Oyekola Peter Oluwatosin is a researcher at the forefront of applying artificial intelligence to industrial infrastructure, with a primary focus on computer vision and robotics for structural health monitoring. His most cited work, "Application of Computer Vision in Pipeline Inspection Robot" (2021, 7 citations), addresses a critical challenge in industrial maintenance: the detection of ageing, corrosion, cracks, and mechanical defects in pipes that can lead to catastrophic leaks. By integrating computer vision algorithms with robotic platforms, Oluwatosin has pioneered methods that enable automated, non-destructive inspection of hard-to-reach industrial structures, significantly improving safety and reducing downtime. His contributions bridge the gap between theoretical AI and practical engineering, offering scalable solutions for real-world asset management. With a growing citation footprint, his research is gaining traction among engineers and roboticists seeking to prevent fatal industrial failures through intelligent automation. Oluwatosin’s work not only advances the field of inspection robotics but also underscores the transformative potential of AI in safeguarding critical infrastructure.