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Chandrashekar, Deepak (2024) Vehicle Number Plate Recognition and the Slot Allocation in a Cloud-Based Automatic Parking Management System under varying Weather Conditions. Masters thesis, Dublin, National College of Ireland.
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Abstract
Rise in the growth parking issues has been caused by the increase in urbanization and the use of cars, most of which clog roads, causing traffic jams, pollution, and time exhaustion. As a solution to the issues mentioned above, we have designed an Intelligent Parking Solution based on IoT, ANPR, and Computer Vision. This system applies real-time data, artificial intelligence, and navigated cloud services to optimize parking organization, minimize parking time, and advance environmentally friendly urban mobility. The key features which includes the real-time parking slot availability, management of entry and exit through number plate recognition, automatic parking slot assignment, automated fee collection, and a centralized database for analytics and business intelligence data. The solution raises user satisfaction, increases income, optimizes flow, and supports urban growth. The YOLO-based models used for parking detection and car number identification allow the system to work under different environmental conditions. Besides these advantages, the system provides an easy-to-use interface for users, promotes the environmental conservation and helps in the development of towns and cities. By enhancing parking management, it supports smart city strategies for improved sustainable urban mobility.
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