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A framework for IoT-enabled environment aware traffic management

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 11 No. 1 (2021)

DOI
10.11591/ijece.v11i1.pp518-527
ISSN
2722-2578, 2088-8708
Published
2021-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Vehicular traffic has increased across all over the world especially in urban areas due to many reasons including the reduction in the cost of vehicles, degradation of the quality of public transport services and increased wealth of people. The traffic congestion created by these vehicles causes many problems. Increased environment pollution is one of the most serious negative effects of traffic congestion. Noxious gases and fine particles emitted by vehicles affect people in different ways depending on their age and present health conditions. Professionals and policy makers have devised schemes for better managing traffic in congested areas. These schemes suffer from many shortcomings including the inability to adapt to dynamic changes of traffic patterns. With the development of technology, new applications like Google maps help drivers to select less congested routes. But, the identification of the best route takes only the present traffic condition on different road segments presently. In this paper the authors propose a system that helps drivers select routes based on the present and expected environment pollution levels at critical points in a given area.

Collaboration network of the authors

3 authors · 3 co-authorship links · 1 across different organisations

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  • University of Moratuwa
  • University of Wasit
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>A framework for IoT-enabled environment aware traffic management</dc:title><dc:creator>Mohamed Firdhous, Mohamed Fazil</dc:creator><dc:creator>Sudantha, B. H.</dc:creator><dc:creator>Hussien, Naseer Ali</dc:creator><dc:description>&lt;jats:p&gt;Vehicular traffic has increased across all over the world especially in urban areas due to many reasons including the reduction in the cost of vehicles, degradation of the quality of public transport services and increased wealth of people. The traffic congestion created by these vehicles causes many problems. Increased environment pollution is one of the most serious negative effects of traffic congestion. Noxious gases and fine particles emitted by vehicles affect people in different ways depending on their age and present health conditions. Professionals and policy makers have devised schemes for better managing traffic in congested areas. These schemes suffer from many shortcomings including the inability to adapt to dynamic changes of traffic patterns. With the development of technology, new applications like Google maps help drivers to select less congested routes. But, the identification of the best route takes only the present traffic condition on different road segments presently. In this paper the authors propose a system that helps drivers select routes based on the present and expected environment pollution levels at critical points in a given area.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2021-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v11i1.pp518-527</dc:identifier><dc:identifier>10.11591/ijece.v11i1.pp518-527</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 11 No 1 (2021); 518</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/22084/14512</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>