Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery

Nowadays, with the growing number of vehicles in Malaysia, traffic congestion at junctions has become a serious issue among motorists. The density of vehicles is increasing day by day, thus, there is a need of adaptive traffic signals which are able to do real time monitoring of traffic density inst...

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Main Author: Mohamad Jeffery, Mutmainnah Radhiah
Format: Student Project
Language:English
Published: 2020
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/104903/1/104903.pdf
https://ir.uitm.edu.my/id/eprint/104903/
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Institution: Universiti Teknologi Mara
Language: English
id my.uitm.ir.104903
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spelling my.uitm.ir.1049032024-10-23T02:03:08Z https://ir.uitm.edu.my/id/eprint/104903/ Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery Mohamad Jeffery, Mutmainnah Radhiah Detectors. Sensors. Sensor networks Nowadays, with the growing number of vehicles in Malaysia, traffic congestion at junctions has become a serious issue among motorists. The density of vehicles is increasing day by day, thus, there is a need of adaptive traffic signals which are able to do real time monitoring of traffic density instead of depending on sensors and hardwired at the time of installation. This study describes a system which make used of image processing in controlling the traffic in an effective manner by taking images of each lane at a junction. Basically, more time is allocated for the vehicles on the densest road to pass compared to other less dense road. A step by step of image acquisition and image processing with several methods used in MATLAB is explained in this study. Basically, the processed image is matched with the template image by using feature based image matching technique and the priorities of having green signal is given to the densest lane while the other lanes are given their green signal based on their decreasing priorities. In doing so, the complete flow of image acquisition, image processing, image matching and the allocation of green signal by using four sample of images (lane 1, lane 2, lane 3 and lane 4) with different traffic density is discussed with proper schematics. The Arduino is used as a microcontroller which responsible in controlling the changes of each signal as well as the duration of the traffic lights signal based on the traffic density at each particular lane. The outcome of this study shows that the smart traffic light control system could improve traffic congestion at junction and avoid the time of green light being wasted on an empty road. This could benefit the motorists from wasting their time on the road waiting for their green signal. 2020-07 Student Project NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/104903/1/104903.pdf Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery. (2020) [Student Project] (Unpublished)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Detectors. Sensors. Sensor networks
spellingShingle Detectors. Sensors. Sensor networks
Mohamad Jeffery, Mutmainnah Radhiah
Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery
description Nowadays, with the growing number of vehicles in Malaysia, traffic congestion at junctions has become a serious issue among motorists. The density of vehicles is increasing day by day, thus, there is a need of adaptive traffic signals which are able to do real time monitoring of traffic density instead of depending on sensors and hardwired at the time of installation. This study describes a system which make used of image processing in controlling the traffic in an effective manner by taking images of each lane at a junction. Basically, more time is allocated for the vehicles on the densest road to pass compared to other less dense road. A step by step of image acquisition and image processing with several methods used in MATLAB is explained in this study. Basically, the processed image is matched with the template image by using feature based image matching technique and the priorities of having green signal is given to the densest lane while the other lanes are given their green signal based on their decreasing priorities. In doing so, the complete flow of image acquisition, image processing, image matching and the allocation of green signal by using four sample of images (lane 1, lane 2, lane 3 and lane 4) with different traffic density is discussed with proper schematics. The Arduino is used as a microcontroller which responsible in controlling the changes of each signal as well as the duration of the traffic lights signal based on the traffic density at each particular lane. The outcome of this study shows that the smart traffic light control system could improve traffic congestion at junction and avoid the time of green light being wasted on an empty road. This could benefit the motorists from wasting their time on the road waiting for their green signal.
format Student Project
author Mohamad Jeffery, Mutmainnah Radhiah
author_facet Mohamad Jeffery, Mutmainnah Radhiah
author_sort Mohamad Jeffery, Mutmainnah Radhiah
title Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery
title_short Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery
title_full Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery
title_fullStr Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery
title_full_unstemmed Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery
title_sort smart control of traffic light system using image processing / mutmainnah radhiah mohamad jeffery
publishDate 2020
url https://ir.uitm.edu.my/id/eprint/104903/1/104903.pdf
https://ir.uitm.edu.my/id/eprint/104903/
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