<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-24T19:31:43Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/115728" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/115728</identifier><datestamp>2021-07-05T14:03:20Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Joseph A. Paradiso.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Haddad, Don Derek</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Program in Media Arts and Sciences (Massachusetts Institute of Technology)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Program in Media Arts and Sciences (Massachusetts Institute of Technology)</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2018-05-23T16:32:09Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2018-05-23T16:32:09Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/115728</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1036986649</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 89-95).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The rise of ubiquitous sensing enables the harvesting of massive amounts of data from the physical world. This data is often used to drive the behavior of devices, but when presented to users, it is most commonly visualized quantitatively, as graphs and charts. Another approach for the representation of sensor network data presents the data within a rich, virtual environment. This thesis introduces the concept of Resynthesizing Reality through the construction of Doppelmarsh, the virtual counterpart of a real marsh located in Plymouth Massachusetts, where the Responsive Environments Group has deployed and maintained a network of environmental sensors. By freely exploring such environments, users gain a vivid, multi-modal, and experiential perspective into large, multi-dimensional datasets. We present a variety of approaches to manifesting data in "avatar landscape", including landscapes generated off live video, tinting frames in correspondence with temperature, or representing sensor history in the appearance and behavior of animals. The concept of virtual lenses is also introduced, which makes it easy to dynamically switch sensor-to-reality mapping from within virtual environments. In this thesis, we describe the implementation and design of Doppelmarsh, present techniques to visualize sensor data within virtual environments, and discuss potential applications for Resynthesizing Reality.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Don Derek Haddad.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">95 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Program in Media Arts and Sciences ()</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Resynthesizing reality : driving vivid virtual environments from sensor networks</dim:field>
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   	&lt;Title>Resynthesizing reality : driving vivid virtual environments from sensor networks&lt;/Title>
   	&lt;Subtitle>Driving vivid virtual environments from sensor networks&lt;/Subtitle>
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   	&lt;PublicationDate>2018&lt;/PublicationDate>
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   	&lt;Abstract>The rise of ubiquitous sensing enables the harvesting of massive amounts of data from the physical world. This data is often used to drive the behavior of devices, but when presented to users, it is most commonly visualized quantitatively, as graphs and charts. Another approach for the representation of sensor network data presents the data within a rich, virtual environment. This thesis introduces the concept of Resynthesizing Reality through the construction of Doppelmarsh, the virtual counterpart of a real marsh located in Plymouth Massachusetts, where the Responsive Environments Group has deployed and maintained a network of environmental sensors. By freely exploring such environments, users gain a vivid, multi-modal, and experiential perspective into large, multi-dimensional datasets. We present a variety of approaches to manifesting data in &amp;quot;avatar landscape&amp;quot;, including landscapes generated off live video, tinting frames in correspondence with temperature, or representing sensor history in the appearance and behavior of animals. The concept of virtual lenses is also introduced, which makes it easy to dynamically switch sensor-to-reality mapping from within virtual environments. In this thesis, we describe the implementation and design of Doppelmarsh, present techniques to visualize sensor data within virtual environments, and discuss potential applications for Resynthesizing Reality.&lt;/Abstract>
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