Mostakim, MoinReza, Md TanzimAbrar, Md. IshtiakSaha, ShawonHalim, Hamim ShabbirShafi, Shoaib Ahamed2023-10-172023-10-17©20229/28/2022ID 17201155ID 18101531ID 18101542ID 18101544http://hdl.handle.net/10361/21858Cataloged from PDF version of thesis.Includes bibliographical references (pages 35-37).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.In 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.48 pagesenBrac 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.Vehicle parking systemR-CNNYOLOv5Machine learningComparative analysisComputational intelligenceIntelligent transportation systemsThesis