Smart IoT-Based Multi-Level Parking System with a Real-Time Guidance Mechanism

Abstract

The development of smart parking systems is a significant topic that has attracted considerable attention from researchers due to their important role in reducing traffic congestion, thereby minimizing environmental pollution, saving drivers’ time and effort, and contributing to improved economic efficiency. This research aims to design and implement a smart parking system featuring a vertical expansion mechanism with multiple levels. Movement between these levels is achieved using an electric elevator, based on the priority of available parking spaces starting from the lower floor. In addition, the system provides a simple user interface that enables users to remotely identify available parking spaces within the facility. This paper presents a model of a multi-story smart parking system based on the Internet of Things (IoT) using an ESP32-S3 development board. Available parking spaces on different levels are detected using LDR sensors, and drivers are then guided to the appropriate space via an LCD display located at the parking entrance. Movement between floors is carried out using an electric elevator that is automatically controlled through a set of infrared sensors (IR) placed inside and outside the elevator. The elevator gate is opened to access the upper floor only when the lower floor is fully occupied and a free space is available on the upper floor. The use of two different types of sensors represents a key aspect of the proposed system, as it achieves a balance between the high performance and reliability of IR sensors and the low cost of LDR sensors. In addition, a web-based interface has been developed to display real-time parking information, allowing drivers to remotely check the availability of parking spaces before arriving at the parking area. The system testing results demonstrated an overall accuracy of approximately 93%, highlighting the effectiveness of sensor diversity in achieving a balanced trade-off between performance and cost. This makes the proposed system both efficient and economically viable.