Ting-Hui Chiang

Papers

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About

Ting-Hui Chiang is a leading researcher in indoor localization and factory automation, with a focus on magnetic field-based positioning systems for Industry 4.0 environments. Their most-cited work, "Magnetic Field-Based Localization in Factories Using Neural Network With Robotic Sampling" (2020, 34 citations), addresses the critical challenge of accurate indoor positioning where GPS signals are unavailable. Chiang pioneered the use of neural networks combined with robotic sampling to leverage ambient magnetic field disturbances for precise localization in complex factory settings. This innovative approach offers a cost-effective alternative to traditional sensor-based methods, enabling reliable tracking of materials and equipment in automated industrial environments. By overcoming the limitations of inertial sensors and other technologies, Chiang's contributions have advanced the practical deployment of localization systems in smart manufacturing. Their work bridges machine learning and industrial robotics, providing scalable solutions that enhance efficiency in factory automation. With growing citation impact, Chiang continues to shape the future of indoor positioning technologies, making them essential reading for researchers and engineers working on Industry 4.0 applications.