The transformation of existing infrastructure into smart cities cannot ignore the smart management of parking systems. Cities with high population density (including Metro cities) especially face the challenge of finding the nearest parking space. The increasing number of vehicles every day aggravates this problem and questions the safety of the vehicles. In this study, the problem of finding parking spaces in smart cities is addressed using an IoT-based methodology. The proposed Intelligent Parking System (IPS) consists of an IoT framework that collects real-time data, sends it to the cloud, and thereby suggests a suitable location for the user to park a car at a nearby location. As part of the framework, a mobile application was developed that allows users to check the availability of nearby parking spaces and subsequently reserve a parking space. This article also describes different use cases for finding a parking space for a person and keeping it in the right place. The proposed system was implemented using Raspberry Pi, NodeMCU, Radio Frequency Identification (RFID) and Infrared (IR) sensors. The results discussed in the following sections support the utility of this IPS.
Smart Parking System, Parking Slots, Smart City, Firebase Real-time Database, IoT