Intelligent Sensing Technologies & IoT
We use ambient UHF RFID signals, multipath effects, and tag measurements to infer activity and environmental state without requiring every object or person to carry a custom device.
RFID systems, intelligent sensing, mobile health, protocol evolution, and human-centered learning technologies.
We use ambient UHF RFID signals, multipath effects, and tag measurements to infer activity and environmental state without requiring every object or person to carry a custom device.
We study how collided responses, I/Q geometry, session dynamics, and reader-side intelligence can improve counting, decoding, and reliability while respecting Gen2-style constraints.
Mobile and ambient sensing projects explore how infrastructure can help detect, interpret, and respond to human state in practical settings.
We instrument learning environments with sensors, AR, and AI to reveal tacit expertise and support training in domains where conventional instruction is too slow or opaque.