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IoT-Enabled Vehicle Speed Monitoring System

Khan, Shafi Ullah; Alam, Noor; Jan, Sana Ullah; Koo, In Soo

Authors

Shafi Ullah Khan

Noor Alam

In Soo Koo



Abstract

Millions of people lose their lives each year worldwide due to traffic law violations, specifically, over speeding. The existing systems fail to report most of such violations due to their respective flaws. For instance, speed guns work in isolation and cannot measure speed of all vehicles on roads at all spatial points. They can only detect the speed of the vehicle the line of sight of the camera. A solution is to deploy a huge number of speed guns at different locations on the road to detect and report vehicles that are over speeding. However, this solution is not feasible because it demands a large amount of equipment and computational resources to process such a big amount of data. In this paper, a speed detection framework is developed to detect vehicles’ speeds with only two speed guns, which can report speed even when the vehicle is not within the camera’s line of sight. The system is specifically designed for an irregular traffic scenario such as that of Pakistan, where it is inconvenient to install conventional systems. The idea is to calculate the average speed of vehicles traveling in a specific region, for instance, between two spatial points. A low-cost Raspberry Pi (RPi) module and an ordinary camera are deployed to detect the registration numbers on vehicle license plates. This hardware presents a more stable system since it is powered by a low consumption Raspberry Pi that can operate for hours without crashing or malfunctioning. More specifically, the entrance and exit locations and the time taken to get from one point to another are recorded. An automatic alert to traffic authorities is generated when a driver is over speeding. A detailed explanation of the hardware prototype and the algorithms is given, along with the setup configurations of the hardware prototype, the website, and the mobile device applications.

Journal Article Type Article
Acceptance Date Feb 14, 2022
Online Publication Date Feb 16, 2022
Publication Date 2022
Deposit Date Feb 18, 2022
Publicly Available Date Feb 18, 2022
Journal Electronics
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 11
Issue 4
Article Number 614
DOI https://doi.org/10.3390/electronics11040614
Keywords internet of things (IoT); artificial intelligence; Raspberry Pi (RPi) module
Public URL http://researchrepository.napier.ac.uk/Output/2846933

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