NeTS: Small: Handheld mm-Accurate Positioning for Wearables

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This proposal develops a system that can track wearables on a user's body with millimeter (mm) accuracy using a handheld device in the user's pocket. Unlike past work, it does so without the need for external infrastructure (e.g. cameras or antenna arrays) or inaccurate, bulky and battery-powered sensors on the body. The proposed work attaches tiny radio frequency identification (RFID) tags that are cheap (costing a few cents) and completely battery-free on to on-body devices or the user's clothing. It then monitors the locations of these tags from a handheld RFID reader in the user's pocket. Unlike past solutions that use bulky, many-antenna RFID readers to locate RFID tags, our approach needs only a single-antenna reader that is both compact and portable. The proposed work will be fully implemented and evaluated on commodity RFID hardware and tags; the solution opens up a rich set of applications. Consider medical tests such as Electroencephalogram (EEG) that can become truly 'wearable', with electrodes on the head positioned automatically without requiring time-consuming manual measurements by a physician. Or consider smart textiles that can now serve as gesture-based interfaces that track a user's movements relative to handheld devices. The proposed research presents three contributions: (1) It proposes a novel approach to disentangle wireless signals traversing different paths from RFID tags to a single-antenna RFID reader - a key challenge in positioning research. It achieves this without relying on bulky, multi-antenna arrays used in past literature. Its core idea is to use signals from teams of RFID tags to separate wireless signal components along different paths. (2) It investigates a solution to locate RFID tags relative to other tags whose positions are known. It seeks to do this using an algorithm that leverages similarity between the wireless signal paths experienced by the tag of interest and neighboring tags whose locations are known. (3) It fully integrates the system to target two applications: i) A wearable EEG system that tracks electrodes on the head using RFID tags attached to them. This eliminates the need for cumbersome manual measurements that doctors perform today before administering the test, allowing EEG to be truly portable. ii) A smart fabric with embedded RFID tags tracked by a mobile device to track the users movements both for continuous fitness monitoring and to create a gesture-based user interface.