Xincong Yang
Papers
4
Total Citations
40
H-Index
3
About
Xincong Yang is a leading researcher at the intersection of construction engineering and artificial intelligence, specializing in computer vision, robotics, and wearable sensing for occupational health and waste management. His pioneering work includes developing a novel system that fuses computer vision with smart insole technologies to estimate construction workers’ physical workload—a breakthrough that has garnered 26 citations and offers a non-invasive, data-driven approach to mitigating ergonomic risks. Yang has also advanced automated construction waste management, proposing a multi-robot system integrating cloud and edge computing (6 citations) and a vision-based localization method using unmanned aerial vehicles (5 citations) to enhance recycling efficiency on large sites. His recent contributions extend to high-precision defect detection in pipe jacking projects, combining YOLOv5-based computer vision with LiDAR point cloud analysis for real-time quality control (3 citations). Through these innovations, Yang is shaping a safer, more sustainable construction industry, demonstrating how intelligent systems can transform traditional practices into data-rich, automated processes.
Research Focus
Key Achievements
Top Papers
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