Xiaoyue Hou
Papers
1
Total Citations
42
H-Index
1
About
Xiaoyue Hou is a researcher specializing in indoor positioning systems and probabilistic localization techniques. Their most significant contribution is the development of a Monte Carlo localization (MCL) algorithm tailored for Bluetooth Low Energy (BLE) devices, as detailed in their highly cited 2017 paper (42 citations). This work advanced Markov localization by applying a probabilistic framework to BLE-based indoor environments, addressing key challenges in accuracy and reliability where traditional GPS fails. By integrating MCL with cost-effective BLE technology, Hou's research has practical implications for smart building navigation, asset tracking, and context-aware services. The paper's sustained citation count reflects its influence on subsequent studies in wireless indoor localization and sensor fusion. Hou's work bridges theoretical probabilistic methods with real-world deployment constraints, offering a scalable solution that has inspired further innovations in low-power, infrastructure-light positioning systems. Their contributions remain foundational for researchers exploring adaptive localization in dynamic indoor spaces.
Research Focus
Key Achievements
Top Papers
- 1