A1 Journal article – refereed

Smart Parking System with Dynamic Pricing, Edge-Cloud Computing and LoRa




List of Authors: Victor Kathan Sarker, Tuan Nguyen Gia, Imed Ben Dhaou, Tomi Westerlund

Publisher: MDPI

Publication year: 2020

Journal: Sensors

Volume number: 20

Issue number: 17

Number of pages: 22

eISSN: 1424-8220

DOI: http://dx.doi.org/10.3390/s20174669

URL: https://www.mdpi.com/1424-8220/20/17/4669


Abstract

A rapidly growing number of vehicles in recent years cause long traffic jams and difficulty in the management of traffic in cities. One of the most significant reasons for increased traffic jams on the road is random parking in unauthorized and non-permitted places. In addition, managing of available parking places cannot achieve the expected reduction in traffic congestion related problems due to mismanagement, lack of real-time parking guidance to the drivers, and general ignorance. As the number of roads, highways and related resources has not increased significantly, a rising need for a smart, dynamic and effective parking solution is observed. Accordingly, with the use of multiple sensors, appropriate communication network and advanced processing capabilities of edge and cloud computing, a smart parking system can help manage parking effectively and make it easier for the vehicle owners. In this paper, we propose a multi-layer architecture for smart parking system consisting of multi-parametric parking slot sensor nodes, latest long-range low-power wireless communication technology and Edge-Cloud computation. The proposed system enables dynamic management of parking for large areas while providing useful information to the drivers about available parking locations and related services through near real-time monitoring of vehicles. Furthermore, we propose a dynamic pricing algorithm to yield maximum possible revenue for the parking authority and optimum parking slot availability for the drivers.


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Last updated on 2021-24-06 at 10:33