Research Project Title:
Learning to Interpret Wireless Location Data
abstract:Smart homes can help users to intuitively control their homes and streamline their everyday lives. WiTrack is a device that uses wireless signals and their reflections to track 3D motion without requiring the use of any additional sensors. It has already been used in smart-home applications such as non-intrusive health monitoring to track a user’s breathing and heart rate and allowing users to control household appliances. To expand the capabilities of WiTrack as a smart-home device, I will be adding a machine learning system to accurately count the number of people in a home, despite WiTrack’s limited range, and make inferences about the setup of a room or house. In addition, the system will recognize specific users, allowing personalized control of the home.
“SuperUROP is a great opportunity to focus on research as an undergraduate. I have worked with this lab as a UROP participant and am really excited about its members’ work. I hope to apply and develop my current knowledge of machine learning and system design as well as practice my communication and presentation skills.”