A Novel Location-Centric IoT-Cloud Based On-Street Car Parking Violation Management System in Smart Cities

Nowadays, in big cities, parking management is a critical issue from both the driver's side and the city government's side. From the driver's side, how to find an available parking lot in a city is a considerable concern. As a result, smart parking systems recently have received great interest, both in academia and industry. From the city government's side, how to manage and distribute such a limited public parking resource efficiently to give every visitor a fair chance of finding an on-street parking lot is also a considerable concern. However, existing studies of smart parking management focus only on assisting the driver's side to find available parking spaces. This study aims to raise a new perspective on such smart parking management and to propose a novel location-centric IoT-cloud-based parking violation management system. The system is designed to assist authoritative officers in finding parking violations easily and recommends the least cost path for officers so that officers can achieve their highest productivity in finding parking violations and issuing parking tickets. Experimental results show that the system not only improves the productivity of officers in finding parking violations and issuing tickets, but also helps reduce the traveling cost of officers and to reduce the average violation period of violating cars considerably.

Medienart:

E-Artikel

Erscheinungsjahr:

2016

Erschienen:

2016

Enthalten in:

Zur Gesamtaufnahme - volume:16

Enthalten in:

Sensors (Basel, Switzerland) - 16(2016), 6 vom: 02. Juni

Sprache:

Englisch

Beteiligte Personen:

Dinh, Thanh [VerfasserIn]
Kim, Younghan [VerfasserIn]

Links:

Volltext

Themen:

Internet of Things
IoT cloud
Journal Article
Parking management system
Parking violation management system
Sensor network
Smart cities

Anmerkungen:

Date Completed 23.01.2018

Date Revised 13.11.2018

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/s16060810

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM261140132