Cooperative Agreement R16AC00131

This Project Grant from the National Science Foundation's $366,083 Engineering program will fund research at the University of Washington to develop a theoretical and algorithmic framework for reliably combining heterogeneous and asynchronous sensor data streams to achieve fast situational awareness and robust feedback response. The research aims to advance foundational knowledge for designing next-generation critical systems that assist humans in data-intensive situations. Specifically, the...

This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program Project Grant award of $599,084 to The Research Foundation for The State University of New York (RF SUNY) aims to enhance the timeliness and power-efficiency of real-time data services. The 3-year project, beginning October 1, 2023, will investigate novel methodologies to improve the capabilities of cost-efficient real-time embedded databases supporting data-intensive applications like smart...

This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program totaling $174,952 will support the development of explainable mathematical frameworks and algorithms for integrating multi-source sensor data from multiple modalities. The awardee, the Regents of the University of Michigan, will receive the funding from May 1, 2022 to April 30, 2024. The project aims to advance fundamental knowledge in explainable data integration through a weakly...

This Project Grant award, provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop a new framework for designing efficient decentralized algorithms that can reliably make decisions in resource-constrained environments while controlling the average proportion of wrong decisions. The $199,991 award, effective December 15, 2024 through November 30, 2025, will explore three main research thrusts: (i)...

This two-year, $271,557 project grant from the National Science Foundation's Office of Integrative Activities and Integrative Activities program (CFDA 47.083) will support the development of a privacy-preserved data fusion framework for personalized recommendation in an edge-assisted Internet of Things smart health network. The primary products and services include designing and building an application to collect sensor data and merge external databases; developing frameworks to address...

This Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $665,053 to San Jose State University Research Foundation (doing business as San Jose State University) for the period of July 15, 2022 through June 30, 2025. The grant supports development of a next-generation cooperative perception system with multi-modal sensing and low-latency communication capabilities....

This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports research at Chapman University to develop a scalable predictive modeling framework that leverages sensor data and failure event information to accurately forecast system failures in industrial settings while preserving data privacy. The $199,106 award, spanning July 2025 to June 2027, aims to enhance predictive accuracy through federated survival analysis, adaptive failure predictions,...

This three-year, $279,334 National Science Foundation project grant funds research at the New Jersey Institute of Technology to develop integrated sensing and normally-off computing architectures for Internet of Things devices. The research focuses on designing processing-in-sensor units and processing-near-sensor units that co-integrate sensing and processing capabilities. These hybrid platforms will feature granularly configurable arithmetic operations to balance accuracy, speed and power...

This $256,000 National Science Foundation STTR Phase I Project Grant to Zsense Systems LLC will support the development of an edge-based oil condition monitoring system for heavy equipment. The system will analyze machine oil conditions on-site to provide comprehensive, real-time information on oil properties and machine health status. Key innovations include an inductive pulse sensing array to detect fine wear debris, microfluidic signal multiplexing technologies, big data analysis and signal...

The National Science Foundation (NSF) awarded a $215,908 Project Grant to the Regents of the University of California, Riverside under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to develop a comprehensive memory management ecosystem called MEMDRIVE. The project aims to optimize memory usage throughout the application and system stack for resource-constrained embedded systems, addressing the "memory wall" problem that limits performance and...