Caring dash: car dashboard symbol recognition system using machine learning technique / Muhammad Afiq Mohd Zailani

A vehicle dashboard is the control panel of a vehicle; it is important to alert to any lights that appear on car dashboard once the driver turns the vehicle on or while the driver is driving. Red lights are used in a car to tell the driver if something's not right and probably needs very quick...

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Main Author: Mohd Zailani, Muhammad Afiq
Format: Student Project
Language:English
Published: 2021
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/104059/1/104059.pdf
https://ir.uitm.edu.my/id/eprint/104059/
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record_format eprints
spelling my.uitm.ir.1040592025-03-07T03:01:10Z https://ir.uitm.edu.my/id/eprint/104059/ Caring dash: car dashboard symbol recognition system using machine learning technique / Muhammad Afiq Mohd Zailani Mohd Zailani, Muhammad Afiq Interactive computer systems Web-based user interfaces. User interfaces (Computer systems) A vehicle dashboard is the control panel of a vehicle; it is important to alert to any lights that appear on car dashboard once the driver turns the vehicle on or while the driver is driving. Red lights are used in a car to tell the driver if something's not right and probably needs very quick attention because continuing could damage the car or put the driver or passengers at risk. Many drivers do not know or understand the symbols that displayed on the car dashboard and what action should be taken. This project is intended to develop a mobile application of a car dashboard symbol Recognition System using Machine Learning Technique for Perodua car users. The method use for the development is Mobile Application Development Life Cycle (MADLC) Model. This application help car user identify what those dashboard symbols indicate when lit and action should be taken. This mobile application will involve camera-based graphical symbol detection. This technique locates and recognizes graphic symbols in clustered environments at the same time, without the need for a segmentation stage. Image recognition makes use of visual search technology to identify objects through the camera of a mobile device. Users can take a picture of a symbol, and get information about the symbols. The application only limits locating nearby workshops rather than acting as an intermediary to the shop services. The user can figure out what those dashboard symbols indicate when lit. This application will help navigate the nearest car workshop. This application is useful especially for all the car drivers out there which can save time and ease their movement anytime at anywhere. 2021 Student Project NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/104059/1/104059.pdf Caring dash: car dashboard symbol recognition system using machine learning technique / Muhammad Afiq Mohd Zailani. (2021) [Student Project] <http://terminalib.uitm.edu.my/104059.pdf> (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 Interactive computer systems
Web-based user interfaces. User interfaces (Computer systems)
spellingShingle Interactive computer systems
Web-based user interfaces. User interfaces (Computer systems)
Mohd Zailani, Muhammad Afiq
Caring dash: car dashboard symbol recognition system using machine learning technique / Muhammad Afiq Mohd Zailani
description A vehicle dashboard is the control panel of a vehicle; it is important to alert to any lights that appear on car dashboard once the driver turns the vehicle on or while the driver is driving. Red lights are used in a car to tell the driver if something's not right and probably needs very quick attention because continuing could damage the car or put the driver or passengers at risk. Many drivers do not know or understand the symbols that displayed on the car dashboard and what action should be taken. This project is intended to develop a mobile application of a car dashboard symbol Recognition System using Machine Learning Technique for Perodua car users. The method use for the development is Mobile Application Development Life Cycle (MADLC) Model. This application help car user identify what those dashboard symbols indicate when lit and action should be taken. This mobile application will involve camera-based graphical symbol detection. This technique locates and recognizes graphic symbols in clustered environments at the same time, without the need for a segmentation stage. Image recognition makes use of visual search technology to identify objects through the camera of a mobile device. Users can take a picture of a symbol, and get information about the symbols. The application only limits locating nearby workshops rather than acting as an intermediary to the shop services. The user can figure out what those dashboard symbols indicate when lit. This application will help navigate the nearest car workshop. This application is useful especially for all the car drivers out there which can save time and ease their movement anytime at anywhere.
format Student Project
author Mohd Zailani, Muhammad Afiq
author_facet Mohd Zailani, Muhammad Afiq
author_sort Mohd Zailani, Muhammad Afiq
title Caring dash: car dashboard symbol recognition system using machine learning technique / Muhammad Afiq Mohd Zailani
title_short Caring dash: car dashboard symbol recognition system using machine learning technique / Muhammad Afiq Mohd Zailani
title_full Caring dash: car dashboard symbol recognition system using machine learning technique / Muhammad Afiq Mohd Zailani
title_fullStr Caring dash: car dashboard symbol recognition system using machine learning technique / Muhammad Afiq Mohd Zailani
title_full_unstemmed Caring dash: car dashboard symbol recognition system using machine learning technique / Muhammad Afiq Mohd Zailani
title_sort caring dash: car dashboard symbol recognition system using machine learning technique / muhammad afiq mohd zailani
publishDate 2021
url https://ir.uitm.edu.my/id/eprint/104059/1/104059.pdf
https://ir.uitm.edu.my/id/eprint/104059/
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score 13.244413