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dc.contributor.advisorSong, Sejun
dc.contributor.authorShorter, Dustin
dc.date.issued2019
dc.date.submitted2019 Spring
dc.descriptionTitle from PDF of title page viewed May 14, 2019
dc.descriptionThesis advisor: Sejun Song
dc.descriptionVita
dc.descriptionIncludes bibliographical references (pages 44-45)
dc.descriptionThesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2019
dc.description.abstractBad road conditions can cause vehicle damage and create hazardous driving conditions. Current reporting methods for bad road conditions is a burden for the reporter, so much so that these conditions might not be reported. With current smartphone technology this reporting method can be greatly improved. Smartphones come with an accelerometer and GPS positioning on-board. Utilizing these sensors, once the application is installed and run, a smartphone user can gather bad road conditions automatically while driving. Then the user can upload the data to the server. These road conditions are then classified and optionally displayed on a map while the user is driving. The potential for finding bad road conditions is greatly increases with crowd sourcing. When the road condition data is analyzed an algorithm is used to determine the size of the bad road condition and how many samples are needed. Even though the smartphone might not have the sampling rate of a dedicated accelerometer it’s potential for gather large amounts of data using crowd sourcing and ease of use outweighs this deficiency.eng
dc.description.tableofcontentsIntroduction -- Background -- Implementation -- Experimentation -- Conclusion
dc.format.extentix, 46 pages
dc.identifier.urihttps://hdl.handle.net/10355/68010
dc.publisherUniversity of Missouri -- Kansas Cityeng
dc.subject.lcshPotholes (Roads)
dc.subject.lcshCrowdsourcing
dc.subject.lcshSmartphones
dc.subject.otherThesis -- University of Missouri--Kansas City -- Computer science
dc.titleCharacterizing Road Conditions via Smart Mobile Crowd Sourcingeng
dc.typeThesiseng
thesis.degree.disciplineComputer Science (UMKC)
thesis.degree.grantorUniversity of Missouri--Kansas City
thesis.degree.levelMasters
thesis.degree.nameM.S. (Master of Science)


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