Complex Activity Recognition using Wearable Sensors

In this project, we develop a wearable system to recognize simple (i.e., sequential) and complex (i.e., interleaved and concurrent) activities in real life. As far as we know, this is the first reported work of a pattern mining approach to complex activity recognition using wearable sensors. We also propose a real-time, hierarchical model to recognize both simple gestures and complex activities.

This work has been reported in PerCom 2009 and IEEE Transactions on Knowledge and Data Engineering.

Tao Gu
Tao Gu
Email: firstname dot lastname AT mq.edu.au
Phone Number: +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.