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Related Experiment Video

Updated: Dec 11, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

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

Victor Kathan Sarker¹, Tuan Nguyen Gia¹, Imed Ben Dhaou^1,2,3

¹Department of Future Technologies, University of Turku, 20500 Turku, Finland.

Sensors (Basel, Switzerland)

|August 23, 2020

Summary

This summary is machine-generated.

Urban traffic congestion is worsened by random parking. This study introduces a smart parking system using sensors and edge-cloud computing to manage parking dynamically, optimizing space and revenue.

Keywords:

IoT LoRa architecture cloud dynamic pricing edge energy-efficient management parking sensor node smart vehicle

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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

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Area of Science:

* Intelligent transportation systems
* Urban planning and traffic management
* Internet of Things (IoT) applications

Background:

* Increasing vehicle numbers lead to severe traffic congestion and parking management challenges in cities.
* Ineffective parking management, lack of real-time guidance, and random parking exacerbate traffic problems.
* Limited infrastructure expansion necessitates innovative smart parking solutions.

Purpose of the Study:

* To propose a multi-layer architecture for an effective smart parking system.
* To enable dynamic parking management and provide real-time guidance to drivers.
* To introduce a dynamic pricing algorithm for optimizing revenue and parking availability.

Main Methods:

* Development of a multi-layer architecture integrating multi-parametric parking slot sensor nodes.
* Utilization of long-range, low-power wireless communication technology.
* Implementation of Edge-Cloud computation for advanced data processing and analysis.

Main Results:

* The proposed system facilitates dynamic management of parking across large urban areas.
* Drivers receive near real-time information on available parking spots and services.
* A dynamic pricing algorithm is introduced to balance revenue generation and parking accessibility.

Conclusions:

* The smart parking system offers an effective solution for urban traffic congestion and parking mismanagement.
* Integration of sensors, wireless technology, and Edge-Cloud computing enhances parking efficiency.
* The dynamic pricing model optimizes both economic returns for authorities and convenience for drivers.