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dc.contributor.advisorMostakim, Moin
dc.contributor.advisorReza, Md Tanzim
dc.contributor.authorAbrar, Md. Ishtiak
dc.contributor.authorSaha, Shawon
dc.contributor.authorHalim, Hamim Shabbir
dc.contributor.authorShafi, Shoaib Ahamed
dc.date.accessioned2023-10-17T03:38:27Z
dc.date.available2023-10-17T03:38:27Z
dc.date.copyright©2022
dc.date.issued2022-09-28
dc.identifier.otherID 17201155
dc.identifier.otherID 18101531
dc.identifier.otherID 18101542
dc.identifier.otherID 18101544
dc.identifier.urihttp://hdl.handle.net/10361/21858
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 35-37).
dc.description.abstractIn the last two decades, the quantity of automobiles has increased dramatically. As a result, utilizing technology effectively to promote convenient parking at public and private locations becomes critical. Conventional parking schemes make it difficult for vehicles to discover available parking spaces. These methods overlook the fact that vehicles are parked on roadways, poor time management during peak hours, and incorrect vehicle parking in a parking space. Furthermore, typical methods in a parking zone need greater human interaction. There is an urgent necessity to create smart parking systems to address the aforementioned challenges. In order to solve parking management in real time and uncertainty, the authors suggest a smart parking system that makes use of IoT and machine learning techniques. The cloud, cameras, and a cyber-physical system are all used in the suggested approach. The creation of a graphical user experience for managers and end-users is a significant task since it necessitates assuring the parking system’s smooth monitoring, management, and security. Furthermore, it must build seamless coordination with a user. The proposed system is effective at wisely dealing with challenges. For instance, it denotes the condition of a parking space to the end-user well beforehand; use of limited and unreserved parking places; incorrect parking; unpermitted parking; proper data analysis of unrestricted and occupied spaces; identifying numerous items in a parking space; fault identification in one or more subsystems; and peak-hour traffic management. The approach saves a lot of time, money, and energy by reducing the need for human involvement.en_US
dc.description.statementofresponsibilityMd. Ishtiak Abrar
dc.description.statementofresponsibilityShawon Saha
dc.description.statementofresponsibilityHamim Shabbir Halim
dc.description.statementofresponsibilityShoaib Ahamed Shafi
dc.format.extent48 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.subjectVehicle parking systemen_US
dc.subjectR-CNNen_US
dc.subjectYOLOv5en_US
dc.subjectMachine learningen_US
dc.subjectComparative analysisen_US
dc.subject.lcshComputational intelligence
dc.subject.lcshIntelligent transportation systems
dc.titleIntelligent parking system using machine learningen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB.Sc. in Computer Science and Engineering


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