Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Traffic congestion is a growing challenge in urban areas, significantly contributing to fuel wastage, increased pollution, and economic losses. A major contributor to congestion is the inefficient allocation of parking spaces. This paper explores the potential of AI-powered smart parking systems to alleviate congestion by optimizing parking space allocation in real time. Using machine learning, computer vision, and IoT sensors, these systems can dynamically manage parking availability and guide drivers to open spots efficiently. We review existing AI-based parking solutions, discuss their advantages and challenges, and propose a framework for future smart parking implementation
"AI-Powered Smart Parking: Reducing Traffic Congestion Through Intelligent Allocation ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.b557-b569, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504169.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator