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dc.contributor.advisorJoseph A. Paradiso.en_US
dc.contributor.authorAzaria, Asaphen_US
dc.contributor.otherProgram in Media Arts and Sciences (Massachusetts Institute of Technology)en_US
dc.date.accessioned2017-03-20T19:40:48Z
dc.date.available2017-03-20T19:40:48Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/107575
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2016.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 117-124).en_US
dc.description.abstractCues from the physical environment are constantly sensed and interpreted - unconsciously finding their way into our cognitive schemas and influencing our perceptions and experiences. Manipulating them has been shown to be powerful, affecting cognitive performance, mood and even physiology. Inspired by this, we propose a workspace capable of dynamically transforming its ambiance. This work presents the Digital Cubicle - a cubicle workspace which uses lighting, video projection and sound to manipulate its physical characteristics. A set of software tools is developed to create digital compositions in such a workspace, basing the compositions on objective physical measures from existing popular workspaces. Through a set of user studies, we evaluate how these elicit occupant perceptual, cognitive and physiological responses. Detailed in this work, are physiological responses indicating stress development and restoration, with interesting implications for health and wellbeing applications. We develop a sensor data collection infrastructure to complement the workspace's controllable ambiance, with rich, real-time information about the occupant context and state. Leveraging Reinforcement Learning techniques, we present a framework to devise adaptive control agents. These utilise sensor data to recommend and transform the workspace ambiance in a closed-loop fashion. A prototype intelligent agent is implemented, optimising for occupants' heart rate recovery, yet counterbalancing for occupants preferences and requests. Through evaluative simulations, anchored with real occupant data, we demonstrate and discuss the effectiveness of our proposed approach.en_US
dc.description.statementofresponsibilityby Asaph Azaria.en_US
dc.format.extent124 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectProgram in Media Arts and Sciences ()en_US
dc.titleIntelligent ambiance : digitally mediated workspace atmosphere, augmenting experiences and supporting wellbeingen_US
dc.title.alternativeDigitally mediated workspace atmosphere, augmenting experiences and supporting wellbeingen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)en_US
dc.identifier.oclc974646398en_US


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