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Oliver Shih

dblp:95/10703 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 3 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
3 papers
Wireless sensing and localization · 97% Edge and fog computing · 3%
Computer graphics and multimedia
1 paper
Audio and music processing · 100%
Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 100%

Topics — the 11 heaviest of 11, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless sensing and localization
acoustic sensing
0.622019
Can a phone hear the shape of a room? · IPSN 2019
ALPS: A Bluetooth and Ultrasound Platform for Mapping and Localization · SenSys 2015
Wireless sensing and localization
indoor localization
0.422015
Demo: ALPS - The Acoustic Location Processing System · SenSys 2015
ALPS: A Bluetooth and Ultrasound Platform for Mapping and Localization · SenSys 2015
Audio and music processing
room acoustics
0.412019
Can a phone hear the shape of a room? · IPSN 2019
Wireless sensing and localization › indoor localization
acoustic localization
0.212015
Demo: ALPS - The Acoustic Location Processing System · SenSys 2015
Wireless sensing and localization › ranging
acoustic ranging
0.212015
ALPS: A Bluetooth and Ultrasound Platform for Mapping and Localization · SenSys 2015
Wireless sensing and localization › localization algorithms
beacon-based localization
0.212015
ALPS: A Bluetooth and Ultrasound Platform for Mapping and Localization · SenSys 2015
Wireless sensing and localization › range-based localization › time-based localization
time-difference-of-arrival localization
0.212015
Demo: ALPS - The Acoustic Location Processing System · SenSys 2015
Wireless sensing and localization › ranging
time-of-flight ranging
0.212015
Demo: ALPS - The Acoustic Location Processing System · SenSys 2015
Ubiquitous computing and smart environments › smart devices
smart speakers
0.112019
Can a phone hear the shape of a room? · IPSN 2019
Wireless sensing and localization › RF-based localization
BLE localization
0.112015
ALPS: A Bluetooth and Ultrasound Platform for Mapping and Localization · SenSys 2015
Edge and fog computing › mobile edge computing › computation offloading
cloud offloading
0.112015
Demo: ALPS - The Acoustic Location Processing System · SenSys 2015

Methods — techniques the papers use, named apart from their topics

impulse response analysis · 1.1echo arrival time · 1.1trilateration · 0.2time difference of arrival · 0.2multilateration · 0.2calibration · 0.2
YearPublicationVenuePosition
2019 Can a phone hear the shape of a room?
abstract
Understanding the location of acoustically reflective surfaces in a room is a critical component in advanced sound processing. For example, intelligent speakers can use a room's acoustic geometry to improve playback quality, source separation accuracy, and speech recognition. In this paper, we present Synesthesia, a system for capturing the acoustic properties of a room using a single fixed speaker and a mobile phone that records audio at multiple locations. Using the arrival time of echoes, the system is able to reconstruct the position of reflective surfaces like walls and then estimate properties like surface absorption.
Oliver Shih, Anthony Rowe 0001
IPSN1
2015 ALPS: A Bluetooth and Ultrasound Platform for Mapping and Localization
abstract
The proliferation of Bluetooth Low-Energy (BLE) chipsets on mobile devices has lead to a wide variety of user-installable tags and beacons designed for location-aware applications. In this paper, we present the Acoustic Location Processing System (ALPS), a platform that augments BLE transmitters with ultrasound in a manner that improves ranging accuracy and can help users configure indoor localization systems with minimal effort. A user places three or more beacons in an environment and then walks through a calibration sequence with their mobile device where they touch key points in the environment like the floor and the corners of the room. This process automatically computes the room geometry as well as the precise beacon locations without needing auxiliary measurements. Once configured, the system can track a user's location referenced to a map.
Patrick Lazik, Niranjini Rajagopal, Oliver Shih, Bruno Sinopoli, Anthony Rowe 0001
SenSys3
2015 Demo: ALPS - The Acoustic Location Processing System
abstract
We demonstrate the Acoustic Location Processing System (ALPS), a platform that augments BLE proximity beacons with ultrasonic transmitters in a manner that allows for precise and robust indoor localization. {\em ALPS} uses Time-Difference-Of-Arrival (TDOA) and Time-Of-Flight (TOF) ranging to accurately localize mobile devices such as off-the-shelf smartphones and tablets in 2D space. Users inside the demo area will be able to determine their location and can directly plot it relatively to a map of the area using our app on a smartphone. Once a receiving device has determined its initial position, it can synchronize its audio clock with the transmission infrastructure to perform TOF-based localization, which provides similar position accuracy to TDOA based localization with fewer beacons. Multilateration and trilateration processing for each device's location is offloaded onto a cloud-based solver that can provide localization as a service to ALPS and similar TOF/TDOA based systems.
Patrick Lazik, Niranjini Rajagopal, Oliver Shih, Bruno Sinopoli, Anthony Rowe 0001
SenSys3