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@article{201516,
        author = {Sanket S. Rathod and Tejal Bagul},
        title = {SMART PARK.AI: Smart Parking Management System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {10345-10348},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201516},
        abstract = {In Urban areas and commercial hubs, parking process plays a integral role to control transport system and for the convenience of drivers. traditionally, searching for empty parking slots to park vehicle was depend on manual tickets and physically keeping watch by security guards which cause wastage of time. Due to manual methods, leads to traffic congestion which results in wastage of fuel on a large scale and increase in human errors during the allocation of parking slots. Due to development in Artificial Intelligence (AI) and Internet of Things (IOT), many urban areas are now shifted towards Smart Parking Management Systems. Automated parking System enables drivers to view acquirable spaces online, mobile applications help drivers can reserve seats in advance to track their availability and for reaching one's destination in real-time. The administrators of the system manage the utilization of parking spaces. They help to monitor tenancy rate computerizes billing and produce analytical reports through a integrated cloud database. Recently researchers have also discovered the combination of 'Deep learning ' and predictive analytics to improve the accuracy of vehicle identification and demand forecasting. This review paper examines numerous research studies related to smart parking automaton systems. The analysis primarily focuses on technologies employed (such as sensors and cameras) the system's features, its benefits, and thew limitations of current solutions. is study also identifying research gaps and sheds light on potential developments in future advanced, 'perspective-based' parking management systems.},
        keywords = {Smart Parking System, Parking Automation, IoT-Based System, Machine Learning, Urban Technology, Convolutional Neural Networks (CNN).},
        month = {May},
        }