Jui-Yu Cheng
Papers
1
Total Citations
6
H-Index
1
About
Jui-Yu Cheng is a researcher whose work sits at the intersection of wireless communication, indoor positioning systems, and intelligent data processing. His key research areas include ZigBee-based localization, location fingerprinting methodologies, and the application of neural networks to enhance spatial accuracy. Cheng's most notable contribution is a pioneering ZigBee indoor positioning scheme that leverages a signal-index-pair data preprocess method to significantly improve precision. This work, published in 2010, introduced a four-stage workflow: constructing a location fingerprint table, training a neural network-based locating model, and preprocessing raw signal data to filter noise and enhance reliability. Though the paper has accumulated 6 citations, its conceptual framework has informed subsequent developments in indoor navigation and IoT-based tracking systems. Cheng's approach exemplifies how intelligent preprocessing can bridge the gap between raw sensor data and practical positioning accuracy, making his work a foundational reference for researchers exploring cost-effective, infrastructure-light localization solutions. His contributions remain relevant for students and engineers working on smart environments, asset tracking, and context-aware computing.
Research Focus
Key Achievements
Top Papers
- 1