WearID: RFID Wristband Reader
Deepak Ganesan, Ph.D.
Advances in RFID technology are opening up a myriad of commercial applications related to identifying and interacting with objects, from home automation and health and wellness to augmented reality and tele-rehabilitation. Passive UHF RFID readers are a particularly attractive option due to their low cost and no maintenance; however, their limited range necessitates the use of many readers to cover a single large room, an expensive and labor-intensive process. This invention, known as WearID, overcomes the traditional limitations of UHF RFID readers through end-to-end design innovation, optimizing the wearable reader for low power, form-factor, and performance. WearID is able to detect grasping, releasing, touching, and passing near tagged objects.
• Consumes 6x less power than best-in-class commercial readers • Provides 3D coverage 20 – 30 centimeters away from tagged objects, even with body blockage • Detects and classifies various hand-based interactions through machine learning: grasping, releasing, touching, and passing by
• IoT • Mobile health • Home automation and security • Augmented reality • Eldercare
Deepak Ganesan is a Professor in the Department of Computer Science at UMass Amherst. His research focuses on ultra-low power wireless communication via backscatter, novel platforms and algorithms for mobile and wearable health sensing, learning and inference on multi-modal sensor data, and micro-powered sensors. Dr. Ganesan leads the UMass Sensors Research Group.
Available for Licensing and/or Sponsored Research
UMA 17-020
Patent Pending
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