Designing of RFID-based IoT model for Automated Parking System with Mobile Communication

Abstract

Automated parking systems (APS) have emerged as an innovative solution to address the growing demand for parking spaces in urban environments, where land scarcity and congestion are major concerns. This review explores the evolution, benefits, and challenges of implementing APS. The primary objective of automated parking is to enhance space utilization and reduce human intervention by relying on advanced technologies such as sensors, robotics, and artificial intelligence. However, it also introduced challenges such as environmental degradation, increased emissions, and road accidents. Among these issues, parking congestion in cities has become a significant concern. The difficulty of finding parking spots contributes to time wastage, fuel consumption, and increased pollution. SPS have emerged as a solution, leveraging technologies like RFID, IoT, and computer vision to optimize parking management. These systems enhance parking efficiency, reduce traffic congestion, and minimize environmental impact through real-time data and predictive analytics. Various SPS approaches—such as Wireless Sensor Networks (WSN), machine learning, and deep learning—aid in parking lot monitoring and occupancy prediction, improving both user experience and urban traffic flow. The integration of such smart systems is crucial in mitigating the parking challenges of modern cities.