Kaiyue Qiu

Beijing University of Civil Engineering and Architecture, Toronto Metropolitan University

Papers

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About

Kaiyue Qiu is a researcher specializing in indoor positioning technologies, with a particular focus on leveraging the Earth's geomagnetic field for high-precision localization in complex environments. Her work addresses the challenge of GPS-denied indoor spaces by exploiting the local anomalies in magnetic fields caused by steel structures and ferromagnetic materials. Qiu's major contributions include the development of a joint algorithm combining particle filters and Dynamic Time Warping (DTW), which significantly improves the accuracy and robustness of geomagnetic positioning systems. Her 2018 paper on this method has garnered 13 citations, establishing a foundation for subsequent work. She further advanced the field by applying back-propagation neural networks to geomagnetic positioning, as detailed in her 2020 study (3 citations), demonstrating the potential of machine learning to enhance indoor navigation. Qiu's research is notable for its practical implications in robotics and ubiquitous computing, offering a cost-effective, infrastructure-free alternative to traditional indoor positioning systems. Her innovative integration of signal processing and neural network techniques continues to influence the development of reliable indoor localization solutions.