Zao-Hung Sun

National Yang Ming Chiao Tung University

Papers

1

Total Citations

34

H-Index

1

About

Dr. Zao-Hung Sun is a leading researcher in indoor localization and factory automation, with a focus on overcoming the limitations of GPS-denied environments. His most impactful work, "Magnetic Field-Based Localization in Factories Using Neural Network With Robotic Sampling" (2020, 34 citations), pioneers a novel approach that leverages ambient magnetic fields and neural networks for precise positioning in industrial settings. By integrating robotic sampling, Dr. Sun’s method addresses the critical challenge of material and item tracking in smart factories, directly supporting the goals of Industry 4.0. His research bridges sensor fusion, machine learning, and robotics, offering scalable solutions that bypass traditional reliance on inertial sensors or audio signals. With growing recognition for his contributions to practical, low-cost localization, Dr. Sun’s work is shaping the future of automated manufacturing and logistics. His innovative use of magnetic field mapping has been cited as a key reference for researchers exploring robust indoor positioning systems, marking him as a rising authority in the field.

Research Focus

Key Achievements

1
H-Index
1
Papers
34
Total Citations
34
Avg Citations/Paper
🏆 Most Cited Paper
Magnetic Field-Based Localization in Factories Using Neural Network With Robotic Sampling
34 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: National Yang Ming Chiao Tung University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago