Project Grant 2306789

Award Date 8/15/23
Completion Date 7/31/27
Dollars Obligated $300K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Auburn University, AL 36849, USA
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This is a Project Grant awarded by the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070). The $299,708 grant, with a period of performance from August 15, 2023 to July 31, 2027, supports collaborative research to develop AI-driven radio frequency identification (RFID) sensing techniques for smart health monitoring applications. The research aims to create more affordable, comfortable,...
The National Science Foundation (NSF) awarded a $299,612 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to The Johns Hopkins University to develop AI-driven Radio Frequency Identification (RFID) sensing systems for smart health monitoring applications. The 4-year project aims to create more affordable, comfortable, and accessible health monitoring solutions by leveraging advances in the Internet of Things and machine learning/artificial...
This Project Grant award of $300,000.00 from the National Science Foundation's Division of Information and Intelligent Systems will fund a collaborative research effort led by Florida International University (FIU) to develop AI-driven RFID sensing techniques for smart health applications. The project aims to create more affordable, comfortable, and accessible health monitoring systems by leveraging advances in the Internet of Things and machine learning/AI. The research will focus on addressing...
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This Project Grant award for $299,997.00 from the National Science Foundation's Computer and Information Science and Engineering Program (CFDA 47.070) supports a collaborative research effort led by Auburn University. The project aims to develop AI-driven radio frequency identification (RFID) sensing techniques to enable more affordable, comfortable, and accessible smart health monitoring systems. The key products and services to be delivered include:

  • Investigating challenges and performance limits of RFID-based sensing systems for health applications
  • Developing RFID-based monitoring techniques for respiration rate, pulmonary function tests, and heartbeat signals
  • Developing RFID-based systems for pose monitoring, activity recognition, and Parkinson's disease detection
  • Creating robust and fair federated learning models to handle health data for these RFID-based monitoring applications

The research will focus on two important smart health applications: Parkinson's disease detection and breathing-based interstitial lung disease detection. The project will also develop new educational courses and provide hands-on experience for students in these cutting-edge wireless sensing, deep learning, and smart health technologies.

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