Loading…

Smart Drive Safe: Harnessing CNN for Enhanced Traffic Sign Recognition and Voice Alerts

Traffic signs secure their safety on the roads and the protection of others around them; everyone must be aware of traffic signs and other aspects of road safety. Traffic sign detection is a highly relevant computer vision problem that forms the basis of numerous applications in sectors like the aut...

Full description

Saved in:
Bibliographic Details
Main Authors: Priya, D. Divya, Chinnasamy, P., Ayyasamy, Ramesh Kumar, Kiran, Ajmeera, A Jalil, Norazira Binti, Sangodiah, Anbuselvan
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 1920
container_issue
container_start_page 1915
container_title
container_volume
creator Priya, D. Divya
Chinnasamy, P.
Ayyasamy, Ramesh Kumar
Kiran, Ajmeera
A Jalil, Norazira Binti
Sangodiah, Anbuselvan
description Traffic signs secure their safety on the roads and the protection of others around them; everyone must be aware of traffic signs and other aspects of road safety. Traffic sign detection is a highly relevant computer vision problem that forms the basis of numerous applications in sectors like the automotive industry. Between classes, traffic signs differ widely in terms of colour, shape, and the use of pictograms or text. The project's classification of traffic signs in an image into various categories is based on a deep neural network model. IoT devices that capture traffic signs and notify users of them are used to build a model.
doi_str_mv 10.1109/ICESC60852.2024.10690129
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_10690129</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10690129</ieee_id><sourcerecordid>10690129</sourcerecordid><originalsourceid>FETCH-ieee_primary_106901293</originalsourceid><addsrcrecordid>eNqFjrFOwzAQQA0SEhXNHzDcDzSc7TrpsaEQVJYOpCpjZaXncFXrIDtC4u_pADPTG97wnlKgsdQa6eG1abumwpUzpUGzLDVWhNrQlSqoppV1aGuipbtWM0NULZx19a0qcj4iojUXq3Gm3ruzTxM8J_li6HzgR1j7FDlniQM0mw2EMUEbP3zs-QDb5EOQHjoZIrxxPw5RJhkj-HiA3Sg9w9OJ05Tn6ib4U-bil3fq_qXdNuuFMPP-M8kl-73_e7b_6B9D_EQx</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Smart Drive Safe: Harnessing CNN for Enhanced Traffic Sign Recognition and Voice Alerts</title><source>IEEE Xplore All Conference Series</source><creator>Priya, D. Divya ; Chinnasamy, P. ; Ayyasamy, Ramesh Kumar ; Kiran, Ajmeera ; A Jalil, Norazira Binti ; Sangodiah, Anbuselvan</creator><creatorcontrib>Priya, D. Divya ; Chinnasamy, P. ; Ayyasamy, Ramesh Kumar ; Kiran, Ajmeera ; A Jalil, Norazira Binti ; Sangodiah, Anbuselvan</creatorcontrib><description>Traffic signs secure their safety on the roads and the protection of others around them; everyone must be aware of traffic signs and other aspects of road safety. Traffic sign detection is a highly relevant computer vision problem that forms the basis of numerous applications in sectors like the automotive industry. Between classes, traffic signs differ widely in terms of colour, shape, and the use of pictograms or text. The project's classification of traffic signs in an image into various categories is based on a deep neural network model. IoT devices that capture traffic signs and notify users of them are used to build a model.</description><identifier>EISSN: 2996-5357</identifier><identifier>EISBN: 9798350379945</identifier><identifier>DOI: 10.1109/ICESC60852.2024.10690129</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cameras ; Convolutional neural network ; datasets ; Hardware ; Image color analysis ; Industries ; Internet of Things ; object detection ; Protection ; Real-time systems ; Road safety ; Shape ; Speech recognition ; Traffic Sign Recognition ; Traffic signs ; Voice alert</subject><ispartof>2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC), 2024, p.1915-1920</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10690129$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10690129$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Priya, D. Divya</creatorcontrib><creatorcontrib>Chinnasamy, P.</creatorcontrib><creatorcontrib>Ayyasamy, Ramesh Kumar</creatorcontrib><creatorcontrib>Kiran, Ajmeera</creatorcontrib><creatorcontrib>A Jalil, Norazira Binti</creatorcontrib><creatorcontrib>Sangodiah, Anbuselvan</creatorcontrib><title>Smart Drive Safe: Harnessing CNN for Enhanced Traffic Sign Recognition and Voice Alerts</title><title>2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC)</title><addtitle>ICESC</addtitle><description>Traffic signs secure their safety on the roads and the protection of others around them; everyone must be aware of traffic signs and other aspects of road safety. Traffic sign detection is a highly relevant computer vision problem that forms the basis of numerous applications in sectors like the automotive industry. Between classes, traffic signs differ widely in terms of colour, shape, and the use of pictograms or text. The project's classification of traffic signs in an image into various categories is based on a deep neural network model. IoT devices that capture traffic signs and notify users of them are used to build a model.</description><subject>Cameras</subject><subject>Convolutional neural network</subject><subject>datasets</subject><subject>Hardware</subject><subject>Image color analysis</subject><subject>Industries</subject><subject>Internet of Things</subject><subject>object detection</subject><subject>Protection</subject><subject>Real-time systems</subject><subject>Road safety</subject><subject>Shape</subject><subject>Speech recognition</subject><subject>Traffic Sign Recognition</subject><subject>Traffic signs</subject><subject>Voice alert</subject><issn>2996-5357</issn><isbn>9798350379945</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2024</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNqFjrFOwzAQQA0SEhXNHzDcDzSc7TrpsaEQVJYOpCpjZaXncFXrIDtC4u_pADPTG97wnlKgsdQa6eG1abumwpUzpUGzLDVWhNrQlSqoppV1aGuipbtWM0NULZx19a0qcj4iojUXq3Gm3ruzTxM8J_li6HzgR1j7FDlniQM0mw2EMUEbP3zs-QDb5EOQHjoZIrxxPw5RJhkj-HiA3Sg9w9OJ05Tn6ib4U-bil3fq_qXdNuuFMPP-M8kl-73_e7b_6B9D_EQx</recordid><startdate>20240807</startdate><enddate>20240807</enddate><creator>Priya, D. Divya</creator><creator>Chinnasamy, P.</creator><creator>Ayyasamy, Ramesh Kumar</creator><creator>Kiran, Ajmeera</creator><creator>A Jalil, Norazira Binti</creator><creator>Sangodiah, Anbuselvan</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20240807</creationdate><title>Smart Drive Safe: Harnessing CNN for Enhanced Traffic Sign Recognition and Voice Alerts</title><author>Priya, D. Divya ; Chinnasamy, P. ; Ayyasamy, Ramesh Kumar ; Kiran, Ajmeera ; A Jalil, Norazira Binti ; Sangodiah, Anbuselvan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_106901293</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Cameras</topic><topic>Convolutional neural network</topic><topic>datasets</topic><topic>Hardware</topic><topic>Image color analysis</topic><topic>Industries</topic><topic>Internet of Things</topic><topic>object detection</topic><topic>Protection</topic><topic>Real-time systems</topic><topic>Road safety</topic><topic>Shape</topic><topic>Speech recognition</topic><topic>Traffic Sign Recognition</topic><topic>Traffic signs</topic><topic>Voice alert</topic><toplevel>online_resources</toplevel><creatorcontrib>Priya, D. Divya</creatorcontrib><creatorcontrib>Chinnasamy, P.</creatorcontrib><creatorcontrib>Ayyasamy, Ramesh Kumar</creatorcontrib><creatorcontrib>Kiran, Ajmeera</creatorcontrib><creatorcontrib>A Jalil, Norazira Binti</creatorcontrib><creatorcontrib>Sangodiah, Anbuselvan</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library Online</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Priya, D. Divya</au><au>Chinnasamy, P.</au><au>Ayyasamy, Ramesh Kumar</au><au>Kiran, Ajmeera</au><au>A Jalil, Norazira Binti</au><au>Sangodiah, Anbuselvan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Smart Drive Safe: Harnessing CNN for Enhanced Traffic Sign Recognition and Voice Alerts</atitle><btitle>2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC)</btitle><stitle>ICESC</stitle><date>2024-08-07</date><risdate>2024</risdate><spage>1915</spage><epage>1920</epage><pages>1915-1920</pages><eissn>2996-5357</eissn><eisbn>9798350379945</eisbn><abstract>Traffic signs secure their safety on the roads and the protection of others around them; everyone must be aware of traffic signs and other aspects of road safety. Traffic sign detection is a highly relevant computer vision problem that forms the basis of numerous applications in sectors like the automotive industry. Between classes, traffic signs differ widely in terms of colour, shape, and the use of pictograms or text. The project's classification of traffic signs in an image into various categories is based on a deep neural network model. IoT devices that capture traffic signs and notify users of them are used to build a model.</abstract><pub>IEEE</pub><doi>10.1109/ICESC60852.2024.10690129</doi></addata></record>
fulltext fulltext_linktorsrc
identifier EISSN: 2996-5357
ispartof 2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC), 2024, p.1915-1920
issn 2996-5357
language eng
recordid cdi_ieee_primary_10690129
source IEEE Xplore All Conference Series
subjects Cameras
Convolutional neural network
datasets
Hardware
Image color analysis
Industries
Internet of Things
object detection
Protection
Real-time systems
Road safety
Shape
Speech recognition
Traffic Sign Recognition
Traffic signs
Voice alert
title Smart Drive Safe: Harnessing CNN for Enhanced Traffic Sign Recognition and Voice Alerts
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-21T11%3A28%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Smart%20Drive%20Safe:%20Harnessing%20CNN%20for%20Enhanced%20Traffic%20Sign%20Recognition%20and%20Voice%20Alerts&rft.btitle=2024%205th%20International%20Conference%20on%20Electronics%20and%20Sustainable%20Communication%20Systems%20(ICESC)&rft.au=Priya,%20D.%20Divya&rft.date=2024-08-07&rft.spage=1915&rft.epage=1920&rft.pages=1915-1920&rft.eissn=2996-5357&rft_id=info:doi/10.1109/ICESC60852.2024.10690129&rft.eisbn=9798350379945&rft_dat=%3Cieee_CHZPO%3E10690129%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-ieee_primary_106901293%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=10690129&rfr_iscdi=true