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dc.contributor.authorWang, Yue
dc.contributor.authorZhang, Jingxuan
dc.date.accessioned2020-08-10T19:48:47Z
dc.date.available2020-08-10T19:48:47Z
dc.date.issued2020-05
dc.identifier.otherWang_cornell_0058O_10809
dc.identifier.otherhttp://dissertations.umi.com/cornell:10809
dc.identifier.otherZhang_cornell_0058O_10817
dc.identifier.otherhttp://dissertations.umi.com/cornell:10817
dc.identifier.urihttps://hdl.handle.net/1813/70216
dc.description29 pages
dc.description.abstractWe are looking forward to designing an in-car recording system with multiple data streams that can help researchers create a new driving experience for the future. With AutoRec, a recording system embedded in the car, we can record a variety of data ranging from the car’s geolocation to the physical behavior and biological data of the driver and the passenger. Through timestamp all these different streams of data, we get a comprehensive idea of all the events occurring in the vehicle. Using these various types of data, we find efficient ways to enhance peoples’ overall interaction with vehicle. And this system allows all possible extensions and applied for different scenarios, including real driving and autonomous driving experience in simulation room – all these applications will be detailed illustrated in results section. This is the final report for our Specialization Project, which is a two- semester project required for the Connective Media Master program.
dc.language.isoen
dc.titleAUTOREC - AN AUTOMATED DATA LOGGING SYSTEM FOR STUDYING IN-CAR EXPERIENCE
dc.typedissertation or thesis
thesis.degree.disciplineInformation Science
thesis.degree.grantorCornell University
thesis.degree.levelMaster of Science
thesis.degree.nameM.S., Information Science
dc.contributor.chairAzenkot, Shiri
dc.contributor.committeeMemberEstrin, Deborah
dcterms.licensehttps://hdl.handle.net/1813/59810
dc.identifier.doihttps://doi.org/10.7298/4qrm-xv40


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