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Article

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

School of Computer Science, University of Bedfordshire, Luton LU1 3JU, UK
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Sensors 2019, 19(2), 347; https://doi.org/10.3390/s19020347
Received: 14 December 2018 / Revised: 10 January 2019 / Accepted: 13 January 2019 / Published: 16 January 2019
(This article belongs to the Special Issue Internet of Things and Machine-to-Machine Communication)
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. View Full-Text
Keywords: WSN; MAC; slotted ALOHA; beacon; Arduino; Raspberry Pi; GPS (Global Positioning System) WSN; MAC; slotted ALOHA; beacon; Arduino; Raspberry Pi; GPS (Global Positioning System)
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MDPI and ACS Style

Handscombe, J.; Yu, H.Q. Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System. Sensors 2019, 19, 347. https://doi.org/10.3390/s19020347

AMA Style

Handscombe J, Yu HQ. Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System. Sensors. 2019; 19(2):347. https://doi.org/10.3390/s19020347

Chicago/Turabian Style

Handscombe, Jonathon, and Hong Q. Yu. 2019. "Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System" Sensors 19, no. 2: 347. https://doi.org/10.3390/s19020347

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