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Augmenting Mobile and Ubiquitous Int...

Zhang, Chi.

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Augmenting Mobile and Ubiquitous Interactions with Computational Light Sensing.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Augmenting Mobile and Ubiquitous Interactions with Computational Light Sensing./
Author:	Zhang, Chi.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	261 p.
Notes:	Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.
Contained By:	Dissertation Abstracts International79-04B(E).
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10689165
ISBN:	9780355540192

Augmenting Mobile and Ubiquitous Interactions with Computational Light Sensing.
Zhang, Chi.

Augmenting Mobile and Ubiquitous Interactions with Computational Light Sensing. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 261 p.

Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2017.

The past decade has witnessed the bloom of billions of mobile and ubiquitous computing devices. They have dispersed into our buildings, our homes, and onto ourselves. These smart devices and wearables bring us unprecedented convenience, by sensing our activities, inferring our intentions, and automating our lives. Unfortunately, they are intrinsically constrained by limited energy supply, tight space, and weak computational power. To benefit mobile and ubiquitous interaction with minimal overhead, this dissertation considers the pervasive light medium, which holds the potential for fine-grained, robust, low-power and real-time sensing. However, constrained sensors designs, lack of infrastructures, and privacy concerns limit its application. Works in this dissertation circumvent these obstacles with novel computational algorithms and rational system designs. Okuli ditches bulky, power-hungry cameras and uses merely 2 low-cost photosensors to locate user's finger with light reflection. Its fine-grained model allows accurate interaction that readily affords virtual off-screen keyboard and handwriting applications. LiTell reuses commercial fluorescent lights to bring accurate and robust visible light localization to today's buildings. It augments smartphone cameras with powerful computational algorithms to extract subtle differences between lights. This allows it to achieve over 90% landmark identification accuracy and decimeter-level localization precision. Pulsar further extends LiTell by replacing cameras with low-power photodiodes. Its novel angle sensing scheme allows it to replace unreliable intensity-based trilateration with accurate triangulation, which enables it to achieve 4X higher accuracy than existing photodiode-based localization systems, while maintaining 5X longer battery life and 2X faster response than camera-based counterparts. LiShield solves the visual privacy problem with smart LED lights. It prevents unauthorized photographing by emitting imperceptible light signals that interfere with camera's operation. Unlike previous privacy frameworks, it can enforce privacy protection without the cooperation of intruders. This makes it a break-through in alleviating privacy concerns in a world filled with smartphone cameras and wireless social networks. Together, these works showcase the great potential of ubiquitous light sensing when coupled with computational algorithms.

ISBN: 9780355540192Subjects--Topical Terms:

649834
Electrical engineering.

Augmenting Mobile and Ubiquitous Interactions with Computational Light Sensing.
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520 $a The past decade has witnessed the bloom of billions of mobile and ubiquitous computing devices. They have dispersed into our buildings, our homes, and onto ourselves. These smart devices and wearables bring us unprecedented convenience, by sensing our activities, inferring our intentions, and automating our lives. Unfortunately, they are intrinsically constrained by limited energy supply, tight space, and weak computational power. To benefit mobile and ubiquitous interaction with minimal overhead, this dissertation considers the pervasive light medium, which holds the potential for fine-grained, robust, low-power and real-time sensing. However, constrained sensors designs, lack of infrastructures, and privacy concerns limit its application. Works in this dissertation circumvent these obstacles with novel computational algorithms and rational system designs. Okuli ditches bulky, power-hungry cameras and uses merely 2 low-cost photosensors to locate user's finger with light reflection. Its fine-grained model allows accurate interaction that readily affords virtual off-screen keyboard and handwriting applications. LiTell reuses commercial fluorescent lights to bring accurate and robust visible light localization to today's buildings. It augments smartphone cameras with powerful computational algorithms to extract subtle differences between lights. This allows it to achieve over 90% landmark identification accuracy and decimeter-level localization precision. Pulsar further extends LiTell by replacing cameras with low-power photodiodes. Its novel angle sensing scheme allows it to replace unreliable intensity-based trilateration with accurate triangulation, which enables it to achieve 4X higher accuracy than existing photodiode-based localization systems, while maintaining 5X longer battery life and 2X faster response than camera-based counterparts. LiShield solves the visual privacy problem with smart LED lights. It prevents unauthorized photographing by emitting imperceptible light signals that interfere with camera's operation. Unlike previous privacy frameworks, it can enforce privacy protection without the cooperation of intruders. This makes it a break-through in alleviating privacy concerns in a world filled with smartphone cameras and wireless social networks. Together, these works showcase the great potential of ubiquitous light sensing when coupled with computational algorithms.
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