Search

RFID localization is considered the key enabler of automating the process of inventory tracking and management for high-performance logistic network. A practical and deployable RFID localization system needs to meet reliability, throughput, and range requirements. This paper presents RF-Chord, the first RFID localization system that simultaneously meets all three requirements. RF-Chord features a one-shot multisine-constructed wideband design that can process RF signal with a 200 MHz bandwidth in real-time to facilitate one-shot localization at scale. In addition, multiple SINR enhancement techniques are designed for range extension. On top of that, a kernel-layer-based near-field localization framework and a multipath-suppression algorithm are proposed to reduce the 99% long-tail errors. Our empirical results show that RF-Chord can localize more than 180 tags 6 m away from a reader within 1 second and with 99% long-tail error of 0.786 m, achieving a 0% miss reading rate and ~0.01% cross-reading rate in the warehouse and fresh food delivery store deployment., Comment: To be published in NSDI 2023

Learning human contexts is critical to the development of many applications, ranging from healthcare, business, to social sciences. Most existing work, however, acquires contextual information in an obtrusive manner – they may require subjects to carry mobile devices, or rely on self or peer report to report data. In this dissertation, we present two unobtrusive techniques that can help us learn important human contextual information including count, location, trajectory, and speech characteristics. We first present SCPL, a radio frequency-based device-free localization technique. SCPL is able to count how many people are in an indoor setting and track their locations by observing how they disturb the wireless radio links in the environment. Second, we present Crowd++, a smartphone-based speech sensing technique, which records a conversation and automatically counts the number of people in the conversation without prior knowledge of their speech characteristics. Both techniques are unobtrusive, low-cost, and private, which can thus enable a large array of important applications that rely upon the knowledge of human contextual information.