Project Grant 2545071
- 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,...
- 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...
- 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...
- This $250,000 National Science Foundation project grant supports research at Florida International University to develop artificial intelligence techniques for radio frequency machine learning and spectrum situational awareness. Led by FIU, the research team will create lifelong incremental learning approaches to spectrum management and dynamic spectrum access enabled by advanced hardware innovations. The team aims to improve spectrum utilization and coexistence of competing users through a...
- This $227,886 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to develop a novel deep sensor array decoding system for high-fidelity remote health monitoring. The project will leverage data-driven deep learning algorithms to decode weak and noisy signals captured remotely from the human body, without requiring a reference signal. By leveraging multi-sensor spatial information, the system will recover the signal of interest from...
- This $200,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports a collaborative research project between Clemson University, Florida Agricultural and Mechanical University, Florida State University, and other partners. The project aims to develop a novel hardware-software co-design communication framework that will enable parallel and spectrum-efficient communication for heterogeneous Internet...
- This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $371,758 to Texas State University to engage undergraduate students in research focused on smart and connected health (SCH) and smart and connected communities (S&CC). The project aims to develop students' disciplinary knowledge and research skills through hands-on experiences in cutting-edge technologies such as machine learning,...
- This Project Grant award, valued at $308,750.00 and provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program, supports research investigating market-driven approaches to radio spectrum management that leverage artificial intelligence (AI). The key objectives of this collaborative research project are to develop AI-powered mechanisms for optimizing spectrum allocation, securing spectrum sensing against adversarial manipulations, and...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award, with CFDA number 47.070, provides $692,847 to the University of Texas at Austin and the University of Texas at San Antonio to develop integrated systems for health and chemical sensing. The project focuses on integrating energy-efficient "weightless neural networks" with cardiac and chemical sensors to create intelligent, wearable health monitoring systems. Key objectives...
- This Project Grant award, valued at $503,930.00 and awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070), supports the development of a wearable sensor network with distributed computing capabilities for advanced health monitoring and biomechanics analysis. The research aims to address key challenges associated with wearable technologies, such as limited computational power, battery capacity, data...
The Project Grant award of $164,110 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports a collaborative research initiative to develop AI-driven radio frequency sensing techniques for smart health monitoring applications. The project aims to create more affordable, comfortable, and accessible health monitoring systems by leveraging advancements in the Internet of Things (IoT) and machine learning/artificial intelligence (ML/AI). The multi-disciplinary research team will investigate fundamental problems in RF sensing and develop novel ML/AI techniques to overcome challenges like noisy RF data and environmental interference. The project will also create a new graduate-level course on deep learning-powered RF health sensing and enhance existing undergraduate and graduate curriculum. Outcomes will be disseminated through publications, conferences, and open-source repositories, with a focus on broadening participation from underrepresented groups.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $164.1k | 8/29/25 |