Muhammad Zohaib Sarwar
Papers
1
Total Citations
66
H-Index
1
About
Dr. Muhammad Zohaib Sarwar is a leading researcher in structural health monitoring and civil infrastructure assessment, with a focus on integrating unmanned aerial vehicles (UAVs) and deep learning for automated inspection. His most-cited work, “Instant bridge visual inspection using an unmanned aerial vehicle by image capturing and geo-tagging system and deep convolutional neural network” (2020, 66 citations), revolutionizes traditional bridge evaluation by replacing manual, labor-intensive methods with a precise, automated system. This approach not only quantifies and localizes structural damages—such as cracks and corrosion—but also reduces subjectivity, time, and costs, marking a significant advancement in infrastructure resilience. Sarwar’s contributions lie at the intersection of computer vision, robotics, and civil engineering, enabling real-time, geo-tagged damage detection that enhances safety and maintenance efficiency. His research has garnered attention for its practical applications in aging infrastructure management, with potential to transform global bridge inspection protocols. By combining UAV technology with deep convolutional neural networks, Sarwar addresses critical challenges in urban sustainability and disaster risk reduction, establishing himself as a key innovator in smart infrastructure systems.
Research Focus
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Top Papers
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