MRI: Acquisition of Omnipercipient Chamber for Gathering Ground Truth and Enabling Research on Smart and Connected Things

点击翻译按钮获取中文摘要

This project supports the acquisition of an omnipercipient chamber (OmniC), with all its sides mounted with a variety of antennas and sensors, for gathering the ground truth (i.e., the information provided by direct observation as opposed to indirect inference) on experiments conducted inside it. This instrument enables the research in diverse areas such as wireless networking, therapeutic and rehabilitation care, robotics and computer vision, cyber physical systems, and augmented and virtual reality. OmniC addresses the needs of many researchers, reduces the cost and effort of pursuing research, furthers inter-disciplinary collaborations, and consequently improves the speed and accuracy of scientific advancement. The labeled ground truth data generated from the experiments conducted inside OmniC would be widely disseminated to help the global research community. This project will also broaden the participation by involving women, minorities, and undergraduates in research, with the help of women investigators and local HBCUs. In addition to assimilating the research results into graduate and undergraduate level courses, this project will showcase the research advances to a wider audience in coordination with the University of South Carolina's outreach activities.The core benefit of this instrument is that it captures the phenomenon being observed coherently across the time, space, and frequency domains. The research activities enabled by OmniC include: i) Devising next-generation mmWave and massive MIMO wireless networks for high throughput and reliability by utilizing channel sparsity; ii) Designing reconfigurable antennas that operate over a broad spectrum from microwave to mmWave; iii) Characterizing thermal dissipation of mmWave devices and developing antenna scheduling schemes for adaptive cooling; iv) Assessing mobility impairments of patients and elderly leveraging the wireless signal reflections and floor vibrations for gait measurement; v) Coordinating autonomous surface vehicles and autonomous aerial vehicles during takeoff and landing under inclement weather and communication constraints; vi) Tracking the movements and poses of subjects across multiple videos and recognizing their emotions by building and training deep learning models; vii) Canceling acoustic noise with IoT relays exploiting the difference in propagation speeds of sound and wireless signals; viii) Supporting ultra-low latency virtual and augmented reality applications over mmWave networks through fast beam alignment protocols. Overall, this instrument taps the common needs and synergy between a variety of research groups across disciplines in advancing research on smart and connected things.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.