Localization in Metro Trains based on Smartphone Sensing

In this project, we present a novel infrastructure-free localization system to locate mobile users in a metro line. Leveraging on crowdsourcing and smartphone sensing, we collect accelerometer, magnetometer and barometer readings, and analyze these sensor data to extract patterns. Through advanced data manipulating techniques, we are able to build the pattern map for the entire metro line, which can then be used for localization. Our field study in 3 metro lines with 55 stations shows that our system achieves an accuracy of over 93% when traveling 3 stations, and 98% when traveling 5 stations.

Tao Gu
Tao Gu
Email: firstname dot lastname AT mq.edu.au
Phone: +61-2-9850-4357
Address: Room 267, 4 Research Park Drive, North Ryde, NSW 2109, Australia

My research interests include Internet of Things, Ubiquitous Computing, Mobile Computing, Embedded AI, Wireless Sensor Networks, and Big Data Analytics.