Event
Ph.D. Research Proposal Exam: Wei-Hsiang Wang
Wednesday, April 3, 2024
4:30 p.m.
AVW2211
Maria Hoo
301 405 3681
mch@umd.edu
ANNOUNCEMENT: Ph.D. Research Proposal Exam
Name: Wei-Hsiang Wang
Committee:
Professor K. J. Ray Liu (Chair)
Professor Min Wu
Professor Furong Huang
Date/time: Wednesday, April 3, 2024 at 4:30 p.m.
Location: 2211 Kim Engineering Building
Title: Wireless Sensing and Analytics for Indoor Daily Activity Monitoring
Abstract:
The rapid advancement of the Internet of Things (IoT) has revolutionized indoor daily activity monitoring by integrating various smart devices and sensors that collect and analyze data related to human activities. Traditional monitoring methods, such as cameras, wearable sensors, and radars, face limitations that restrict their effectiveness and scalability in diverse indoor environments. Recently, WiFi has emerged as a promising wireless sensing tool for its cost-effectiveness, non-intrusiveness, and ubiquity. In this proposal, we particularly focus on sleep monitoring and indoor target localization and tracking for indoor activity monitoring. This proposal first presents a comprehensive framework for non-intrusive daily activity monitoring using commodity WiFi devices, addressing the shortcomings of conventional approaches. We introduce WiResP, a novel, training-free respiratory rate (RR) monitoring system that captures breathing signals even under low signal-to-noise ratio conditions, offering flexible device placement and broader coverage. Our real-world experiments demonstrate WiResP's effectiveness in providing reliable and precise respiration monitoring. Additionally, we propose a novel scheme for indoor target localization, enabling accurate detection and localization of moving humans across multiple rooms with room-level granularity. This system requires only a single receiver and several transmitters, significantly reducing the need for dense device deployment and calibration. For future work, we aim to achieve indoor target tracking with commodity WiFi and several related challenges are discussed in the proposal. In summary, our proposal capitalizes on the widespread availability and cost-effective nature of WiFi to improve daily activity monitoring.
