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dc.contributor.advisorAzad, Dr. A.K.M Abdul Malek
dc.date.accessioned2018-12-27T10:21:24Z
dc.date.available2018-12-27T10:21:24Z
dc.date.copyright2018
dc.date.issued2018-08
dc.identifier.otherID 14321046
dc.identifier.otherID 14221009
dc.identifier.otherID 14221008
dc.identifier.otherID 18321059
dc.identifier.urihttp://hdl.handle.net/10361/11059
dc.descriptionThis thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2018.en_US
dc.descriptionCatalogued from PDF version of thesis.
dc.descriptionIncludes bibliographical references( page 54-55).
dc.description.abstractTraffic congestion in the city of Dhaka is reaching a new pinnacle every day. Owing to numerous private cars and local buses, the gridlocks in Dhaka city can be termed as one of the worst in the world. In a recent study done by Bangladesh University of Engineering and Technology(BUET) and Accident Research Institute (ARI), it was stated that around 5 million working hours are being lost every year in Dhaka city due to traffic gridlocks. This results in a loss of worth Tk.37,000 crore. In order to resolve this issue and help manage the gargantuan problem, we decided to tackle this by the implementation of Kalman Filter in order to predict the level of congestion at a particular road according to time variance of the day. The reason for using Kalman Filter is because its accuracy. Other reasons being that it can be simulated using Matlab and can be constantly updated using the latest data.en_US
dc.description.statementofresponsibilitySamir Karim
dc.description.statementofresponsibilitySoumik Shadman
dc.description.statementofresponsibilityNazmus Sa-Adat
dc.description.statementofresponsibilityMashrur Hasnaen
dc.format.extent88 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectTraffic jamen_US
dc.subjectAwarenessen_US
dc.subjectKalman filteren_US
dc.titleTraffic condition awareness using kalman filter technique with the aid of arduino and matlab embedded system authoren_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Electrical and Electronic Engineering, BRAC University
dc.description.degreeB. Electrical and Electronic Engineering


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