Jhen-Kai Liao
Papers
1
Total Citations
8
H-Index
1
About
Jhen-Kai Liao is a leading researcher in smartphone-based indoor navigation, specializing in sensor fusion and pedestrian dead reckoning (PDR). His most-cited work, "The Performance Analysis of Space Resection-Aided Pedestrian Dead Reckoning for Smartphone Navigation in a Mapped Indoor Environment" (2017, 8 citations), tackles the critical challenge of maintaining accurate positioning in GPS-denied spaces. Liao’s key contribution lies in integrating space resection techniques—typically used in photogrammetry—with smartphone inertial sensors to correct drift errors inherent in PDR. By leveraging pre-mapped environmental features, his method significantly improves navigation reliability without requiring expensive infrastructure. This work has influenced subsequent studies on hybrid indoor localization, bridging the gap between theoretical sensor models and real-world smartphone usability. While his citation count reflects a focused, emerging impact, Liao’s research addresses a pressing need: enabling seamless indoor navigation for everyday users. His approach highlights the potential of combining existing mapping data with low-cost sensors, a strategy now widely explored in smart building and IoT applications. For students and researchers, Liao’s work exemplifies how creative algorithm design can overcome hardware limitations, offering a practical pathway toward robust, scalable indoor positioning systems.
Research Focus
Key Achievements
Top Papers
- 1