A Useful Model-Based System for Forecasting Parking Availability Using IOT

Abstract

The past two decades have witnessed a significant surge in the number of vehicles, emphasizing the need to leverage technology for efficient parking solutions in both public and private spaces. Traditional parking systems present challenges for drivers, including the difficulty of locating available parking spaces, overlooking on-road parking, issues with time management during peak hours, and instances of improper vehicle placement in designated slots. Additionally, these conventional systems rely heavily on human intervention within parking zones. To address these issues, there is a pressing need for the development of Intelligent Parking Systems. In this document, the authors propose an Intelligent Parking System based on the Internet of Things (IoT) to address real-time parking management challenges and uncertainties. The primary objective is to establish seamless coordination with end-users. The proposed system adeptly tackles various challenges, including providing advanced notice of parking slot status to end-users, incorporating both reserved and unreserved parking slots, and conducting real-time analyses of parking space availability. Importantly, the system significantly reduces the necessity for human intervention, resulting in savings in time, cost, and energy. Through the implementation of this proposed system, individuals can proactively determine the availability of parking spaces by consulting LCD displays located outside premises. Furthermore, a dedicated Android application offers a user-friendly platform for users to view all vacant parking slots. This innovative solution represents an intelligent and efficient approach to alleviate the complexities associated with parking management, offering substantial benefits in terms of time, cost, and energy efficiency.