Project Grant 60NANB20D163

This $300,000 Project Grant awarded by the National Science Foundation's Engineering program (CFDA 47.041) aims to develop batteryless technology for Internet of Things (IoT) devices, particularly in wearable applications such as fitness trackers, smartwatches, and medical devices. The project will integrate artificial intelligence (AI) and deep learning techniques to harness the potential of batteryless sensors for personalized data analytics. Key objectives include: Developing new deep...

This SBIR Phase I Project Grant, awarded by the National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program, provides $305,000 to Creathadh Energies LLC to develop a prototype for vibration harvesting technology in wearable devices. The key objectives are to enable human movement vibrations to power commercial applications like wearable heart rate monitors, eliminating the need for battery replacements or recharging. The project will advance scientific and...

The National Science Foundation (NSF) awarded a $400,000 Project Grant under the Engineering program (CFDA 47.041) to the University of Southern California (USC) for the development of a "Non-Resonant Electromagnetic Vibration Energy Harvester with Magnetic Gear for Wearable Technology". The research aims to efficiently generate power from vibration energy associated with human daily activities, such as walking, to power wearable devices and reduce the need for battery recharging or...

This Project Grant award from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program provides $302,668 to Hominin.ai Inc. to develop a software system for real-time monitoring of user health through movement analysis using commercially available wireless headphones. The goal is to translate ordinary human walking patterns into movement-based biomarkers that can identify early indicators of musculoskeletal or neurological diseases, predict health...

This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $1,183,690.00 to The Regents of the University of California, San Francisco (UCSF) to develop personalized machine learning models that can predict adverse health events like substance use and stress-related blood pressure spikes using data from wearable devices like Fitbit and Apple Watch. The innovation of this project lies in...

This National Science Foundation (NSF) Project Grant awarded to Virginia Polytechnic Institute & State University (Virginia Tech), totaling $600,000, supports the development of hardware and software for sustainable and efficient wearable edge intelligence. The project aims to address fundamental accessibility and sustainability challenges of wearable health monitoring devices and artificial intelligence services for underserved communities. Key research focuses include extending the...

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)....

This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $254,369 to Michigan Technological University to develop a wearable device capable of continuously sensing physiological signals for biometric authentication and health monitoring. The project aims to advance cybersecurity, protect user privacy, and support smart healthcare by improving the reliability and accessibility of wearable technologies. The research will explore the use of...

This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $260,000 to The University of Texas Rio Grande Valley (UTRGV) to develop robust deep learning techniques for medical sensor time series data analysis. The key objectives are to: 1) identify input confounders that lead to spurious correlations in time series data, 2) design mitigation strategies to correct these spurious correlations, and 3)...