Development of Parking System for Smart Cities using LoRaWAN, Blockchain, and Deep Learning

Nowadays, data among smart parking lots are susceptible to tampering, while an enormous amount of data is exchanged among multiple stakeholders, increasing issues related to reliability and efficiency, which may result in people having difficulty finding acceptable slots at nearby parking lots and absorbing a longer time for registration at the entry gate. In this work, we present a proposed smart parking system integrated based on LoRaWAN, Blockchain database called BigchainDB, Optical Character Recognition (OCR) using WPOD-NET along with SVM, and Cloud services. The major goal of the proposed system is to gather various parking lots to help decrease deployment time, preserve and share safe information, and create a cutting-edge non-stop platform for client identification under a trusted decentralized system. Based on the results of this research, we discovered an approach for efficient and low-power interaction between components in parking lots, a decentralized blockchain network, and the cloud. Furthermore, this system can handle an enormous number of people using it simultaneously while maintaining a low average delay of approximately in a second.