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Ubiquitous precise tracking: from activity detection over indoor tracking, to outdoor vehicle positioning

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Title
Ubiquitous precise tracking: from activity detection over indoor tracking, to outdoor vehicle positioning
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Ahmed
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Mohamed
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Mohamed Ahmed
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Dimitris
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Martin
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Richard
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Choudhoury
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Romit
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Romit Choudhoury
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Rutgers University
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School of Graduate Studies
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theses
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2021
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2021-01
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English
Abstract
Context awareness and tracking have changed our daily activities and style of living over the last three decades. Many applications have fueled research and industry efforts to establish accurate, energy-efficient, yet scalable and easy to deploy tracking and sensing systems. One of these applications is indoor and outdoor energy saving. For example, precise room occupancy estimation and activity sensing enable better control of indoor amenities such as light, heating, and air conditioning. These indoor applications can be extended to outdoor use for smart cities,e.g., automatic decrease of lighting for empty streets. However, current tracking systems can still not meet the aforementioned stringent requirements, and as a result there are no real world deployments of such applications. For example, conventional wireless tracking relies on WiFi received signal strength, and more recently on channel state information (CSI) offering decimeter level tracking accuracy. However, these tracking systems require either extensive fingerprints collection (wardriving), the knowledge of anchor locations and/or require expensive hardware that prevents wide deployment of such systems. Therefore, these applications with their sensing requirements still demand more accurate and scalable solutions.

This thesis focuses on developing wireless tracking solutions targeting submeter accuracy indoors and meter-level accuracy outdoors by leveraging unconventional wireless signals including visible light and WiFi Fine Time Measurements (FTM). These tracking algorithms can adaptively learn and simultaneously map the environment/anchors while tracking users.

The goal of this research is to propose tracking and context aware sensing systems that can tweak their parameters and map the environment through crowd-sourcing without the need of offline training. In particular, the proposed solutions include: (i) EyeLight, a device-free sensing system based on visible light to enable accurate tracking indoors and provide occupancy estimation, room activity recognition services; This system integrates photosensors with light bulbs easing its deployment compared to existing systems requiring the deployment of photosensors on the floor, (ii) an open platform for experimenting with WiFi fine time measurements and a general, repeatable, and accurate measurement framework for evaluating time-based ranging systems, (iii) Wi-Go, a system that simultaneously tracks vehicles and maps WiFi access point positions by fusing WiFi FTMs, GPS, and odometry information. We believe these three systems enable energy-efficient, continuous, precise and easy to deploy indoor and outdoor tracking and context awareness sensing solutions.
Subject (authority = local)
Topic
Wireless sensing
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Computer Science
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Rutgers University Electronic Theses and Dissertations
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ETD_11439
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1 online resource (xii, 100 pages)
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Ph.D.
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Includes bibliographical references
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ETD doctoral
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rucore10001600001
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Identifier (type = doi)
doi:10.7282/t3-z00m-wg31
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The author owns the copyright to this work.
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Ahmed
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Mohamed
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2021-01-05 17:39:36
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Mohamed Ahmed
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Rutgers University. School of Graduate Studies
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
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Copyright protected
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Open
Reason
Permission or license
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