This paper presents a robust, data-driven framework for intelligent urban mobility, focusing on real-time slot allocation in smart parking ecosystems. By integrating IoT-based sensor networks with optimized resource allocation algorithms, the system dynamically manages parking availability to minimize search time and reduce traffic congestion. The research utilizes real-time data analytics to predict occupancy patterns, providing users with a seamless, user-friendly interface for instant booking and navigation. Experimental results demonstrate a significant improvement in parking space utilization efficiency and a marked reduction in vehicle emissions caused by idling, contributing to the development of sustainable smart city infrastructure.
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2025 Conference Paper, ResearchGate.
https://www.researchgate.net/publication/399751288_An_Optimized_Data-Driven_Approach_for_Real-Time_Slot_Allocation_and_User-Friendly_Access_in_Smart_Parking_System