A study on challenges and solution of car parking for the IOT in cities

Abstract

It is possible to connect billions of devices and services via the Internet of Things (IoT), which has a variety of applications. IoT has become a popular emerging technology in the past few years. There is much discussion about smart car parking in current IoT research. There are more than a million cars on the roads of a modern urban city, but there are not enough parking spaces for them. Furthermore, a growing number of researchers are recommending cloud management of data. While this method is possible, it may pose a problem since raw data from distributed sensors will be sent to the parking area via cloud and will be received back after processing. Data transmission and energy consumption are considered to be expensive aspects of this technique. In this paper, other factors such as traffic congestion on roads and information about nearby car parks are considered in an alternative method for finding unoccupied parking spaces. To reduce the time it takes to find parking spaces, the author proposes a smart car parking system. Additionally, it shows users the status of traffic congestion on roads. The proposed system captures raw data locally and uses data fusion and filtering techniques to extract features, thereby reducing the amount of data transmitted over the network. After being transformed, the data is sent to the cloud for processing and evaluation using machine learning algorithms. As Information technology is becoming increasingly prevalent in society, with smart parking systems rapidly increasing in number two main challenges are highlighted, namely operational issues and technical challenges specific to the project. It is essential to address these challenges from the start in order for the system to perform efficiently in situ. According to all studies conducted in the past decade, traditional smart parking systems do not satisfy the needs of drivers.