Enhancing Urban Mobility: AI-Driven Smart Intelligent Parking Systems for Smart Cities

Abstract

Urbanization and increased vehicle growth pose significant challenges to parking management. making it an important component of smart city infrastructure. traditional parking system It relies on manual supervision or basic sensor technology. It cannot solve problems such as congestion and wastage of fuel. and environmental degradation effectively This paper presents an advanced smart parking system (SIPS) that leverages artificial intelligence (AI), internet of things (IoT), and machine learning for a transformational solution. The proposed system combines real-time dice collection through IoT-based sensors, predictive analysis using machine learning algorithms. and an automatic navigation system for parking lots via a mobile app. Computer vision powered by IA guarantees accurate detection of parking availability. while computation also supports stepwise data processing and continuous communication between stakeholders. The system's innovative features include dynamic allocation of parking waves. Predictive demand management and an improved user experience through real-time updates. Navigation helps and digital payment options Benefits range from reduced search times. Reduce fuel use and reduce carbon emissions to a minimum Promote sustainability and efficient traffic flow. This is despite challenges such as operational costs and data privacy. Integrating emerging technologies such as blockchain, edge computing and automatic vehicles Promising improvements in scalability, accuracy, and safety, the SIPS model exemplifies the potential of technology-based solutions to create more sustainable urban ecosystems. Future research directions involve addressing existing limitations and integrating SIPS into the broader smart city structure. To improve urban mobility and the environment.