Smart Parking System in Smart Cities Based On the Internet of Things and Machine Learning

Smart city parking systems comprehensively depend on operational challenges and technological frameworks such as sensors, RFID, and cloud infrastructures. The main challenges include connectivity issues, security vulnerabilities in RFID-based systems, and the growing demand for real-time booking. This paper proposes an innovative two-stage parking system based on the Internet of Things and machine learning in response to these identified shortcomings. The initial phase integrates Infrared sensors, ESP8266 controllers, and a user-friendly mobile application to enhance parking space management efficiency. The subsequent stage employs Genetic Algorithms and specialized vehicle modification kits, enabling the implementation of self-parking functionalities. The paper outlines detailed methodologies, materials, and outcomes, illustrating the capability for real-time updates on parking availability and optimizing parking space utilization. The system is designed to manage incoming and outgoing cars by collecting and processing data to update parking status with the news of empty lots. In addition, a fully automatic method of paying the parking fee by the user. By leveraging sensor technologies, user-centric applications, and innovative algorithms, the proposed intelligent parking system based on the Internet of Things and machine learning revolutionizes parking space management.