Devi Willieam Anggara

University of Technology Malaysia

Papers

1

Total Citations

4

H-Index

1

About

Devi Willieam Anggara is a researcher at the forefront of robotics and computer vision, with a focus on developing intelligent systems for infrastructure monitoring. Her most-cited work, "Real-Time Crack Classification with Wall-Climbing Robot Using MobileNetV2" (2023), demonstrates a novel integration of deep learning and autonomous robotics. In this study, she engineered a wall-climbing robot capable of real-time crack detection and classification on vertical surfaces, leveraging the lightweight MobileNetV2 architecture for efficient on-board processing. This contribution addresses critical challenges in structural health monitoring, offering a scalable, cost-effective solution for early damage assessment in bridges, buildings, and pipelines. With 4 citations already, her work is gaining traction among researchers in nondestructive testing and field robotics. Anggara’s research bridges practical engineering needs with cutting-edge AI, showcasing how compact neural networks can enable real-time decision-making in constrained robotic platforms. Her achievements highlight a promising trajectory in applying mobile robotics to real-world inspection tasks, making her a notable emerging voice in the intersection of automation and civil infrastructure safety.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Real-Time Crack Classification with Wall-Climbing Robot Using MobileNetV2
4 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Technology Malaysia

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago