Intelligent parking system using machine learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
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| Idioma: | English |
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Brac University
2023
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| Acesso em linha: | http://hdl.handle.net/10361/21858 |
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10361-218582023-10-17T21:02:27Z Intelligent parking system using machine learning Abrar, Md. Ishtiak Saha, Shawon Halim, Hamim Shabbir Shafi, Shoaib Ahamed Mostakim, Moin Reza, Md Tanzim Department of Computer Science and Engineering, Brac University Vehicle parking system R-CNN YOLOv5 Machine learning Comparative analysis Computational intelligence Intelligent transportation systems This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 35-37). 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. Md. Ishtiak Abrar Shawon Saha Hamim Shabbir Halim Shoaib Ahamed Shafi B.Sc. in Computer Science and Engineering 2023-10-17T03:38:27Z 2023-10-17T03:38:27Z ©2022 2022-09-28 Thesis ID 17201155 ID 18101531 ID 18101542 ID 18101544 http://hdl.handle.net/10361/21858 en Brac 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. 48 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Vehicle parking system R-CNN YOLOv5 Machine learning Comparative analysis Computational intelligence Intelligent transportation systems |
| spellingShingle |
Vehicle parking system R-CNN YOLOv5 Machine learning Comparative analysis Computational intelligence Intelligent transportation systems Abrar, Md. Ishtiak Saha, Shawon Halim, Hamim Shabbir Shafi, Shoaib Ahamed Intelligent parking system using machine learning |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Mostakim, Moin |
| author_facet |
Mostakim, Moin Abrar, Md. Ishtiak Saha, Shawon Halim, Hamim Shabbir Shafi, Shoaib Ahamed |
| format |
Thesis |
| author |
Abrar, Md. Ishtiak Saha, Shawon Halim, Hamim Shabbir Shafi, Shoaib Ahamed |
| author_sort |
Abrar, Md. Ishtiak |
| title |
Intelligent parking system using machine learning |
| title_short |
Intelligent parking system using machine learning |
| title_full |
Intelligent parking system using machine learning |
| title_fullStr |
Intelligent parking system using machine learning |
| title_full_unstemmed |
Intelligent parking system using machine learning |
| title_sort |
intelligent parking system using machine learning |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/21858 |
| work_keys_str_mv |
AT abrarmdishtiak intelligentparkingsystemusingmachinelearning AT sahashawon intelligentparkingsystemusingmachinelearning AT halimhamimshabbir intelligentparkingsystemusingmachinelearning AT shafishoaibahamed intelligentparkingsystemusingmachinelearning |
| _version_ |
1814307083421483008 |