Abstract: Parking space management has become extremely difficult due to the sharp rise in urban vehicle ownership, which has increased carbon emissions, wasted fuel, and traffic congestion. Urban mobility is inefficient due to the lack of real-time monitoring, intelligent allocation, and predictive capabilities in traditional parking management systems. In order to maximize parking utilization, this paper introduces a Smart Parking Management System (SPMS) that combines artificial intelligence (AI) and Internet of Things (IoT) sensors. IoTenabled sensors identify the presence of vehicles and send real-time occupancy data, while AI-based algorithms evaluate both live and historical data to forecast availability and direct drivers. digital payments, booking, and navigation are all made possible by a mobile application. Reduced cruising time, better space use, lower emissions, and scalable deployment for smart cities are the goals of the suggested system. Architecture, implementation options, testing methods, assessment metrics, and future directions are all covered in the paper.


Downloads: PDF | DOI: 10.17148/IJARCCE.2025.14915

How to Cite:

[1] Dr. Dinesh D Puri, Mr. Keshav S Chaudhari, "Smart Parking Management System: An IoT and AI-Based Approach for Efficient Urban Mobility," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.14915

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