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This growing demand for parking spaces in urban areas has resulted in increased congestion and inefficient parking space utilization. To address these challenges, a digital parking infrastructure has been proposed. This system employs a network of sensors, cameras, and communication modules to collect real-time parking data, including occupancy status and vehicle movements. The gathered data analysis is facilitated by employing machine learning algorithms to forecast parking demand and optimize parking space allocation. Additionally, the IoT-APS (Adaptive Parking System) provides personalized parking recommendations to drivers based on their preferences and real-time traffic conditions, enhancing the user experience.
Bhorge et al. (Wed,) studied this question.
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