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Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System

There are many methods of collecting traffic flow data, especially using smart phone apps. However, few current solutions balance the need for collecting full route data whilst respecting privacy and remaining low-cost. This project looks into the creation of a wireless sensor network (WSN) that can...

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Detalles Bibliográficos
Autores principales: Handscombe, Jonathon, Yu, Hong Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358924/
https://www.ncbi.nlm.nih.gov/pubmed/30654549
http://dx.doi.org/10.3390/s19020347
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author Handscombe, Jonathon
Yu, Hong Qing
author_facet Handscombe, Jonathon
Yu, Hong Qing
author_sort Handscombe, Jonathon
collection PubMed
description There are many methods of collecting traffic flow data, especially using smart phone apps. However, few current solutions balance the need for collecting full route data whilst respecting privacy and remaining low-cost. This project looks into the creation of a wireless sensor network (WSN) that can balance these requirements in an attempt to negate some of the concerns that come with this type of technology. Our proposed system only collects location data within a defined city area. This data is collected with a randomized identifier, which limits repeated identification of the source vehicle and its occupants. Data collected is shared between vehicle and roadside base stations when the two are in range. To deal with the fluid nature of this scenario, a purposely designed Media Access Control (MAC) protocol was designed and implemented using the beacon-slotted ALOHA (Advocates of Linux Open-source Hawaii Association) mechanism.
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spelling pubmed-63589242019-02-06 Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System Handscombe, Jonathon Yu, Hong Qing Sensors (Basel) Article There are many methods of collecting traffic flow data, especially using smart phone apps. However, few current solutions balance the need for collecting full route data whilst respecting privacy and remaining low-cost. This project looks into the creation of a wireless sensor network (WSN) that can balance these requirements in an attempt to negate some of the concerns that come with this type of technology. Our proposed system only collects location data within a defined city area. This data is collected with a randomized identifier, which limits repeated identification of the source vehicle and its occupants. Data collected is shared between vehicle and roadside base stations when the two are in range. To deal with the fluid nature of this scenario, a purposely designed Media Access Control (MAC) protocol was designed and implemented using the beacon-slotted ALOHA (Advocates of Linux Open-source Hawaii Association) mechanism. MDPI 2019-01-16 /pmc/articles/PMC6358924/ /pubmed/30654549 http://dx.doi.org/10.3390/s19020347 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Handscombe, Jonathon
Yu, Hong Qing
Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System
title Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System
title_full Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System
title_fullStr Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System
title_full_unstemmed Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System
title_short Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System
title_sort low-cost and data anonymised city traffic flow data collection to support intelligent traffic system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358924/
https://www.ncbi.nlm.nih.gov/pubmed/30654549
http://dx.doi.org/10.3390/s19020347
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