ItemConference Paper

Multilingual Voice-Assisted for Traffic Sign Detection and Classification in Adverse Weather Conditions

Title
Multilingual Voice-Assisted for Traffic Sign Detection and Classification in Adverse Weather Conditions
Creator
Krishnendhu, K.; Mathew, Neha Elizabeth; Gunavathi, R.; Johnson, Amala
Description
In a world where millions of people are wounded in auto accidents each year due to negligence, a lack of understanding of traffic laws, and bad weather, there is an urgent need for greater road safety. This is particularly the case in India, where a disproportionately high number of traffic accidents lead to numerous fatalities. Ignoring traffic signs raises these risks and endangers not only vehicles but also passengers and pedestrians. This project addresses the significant issue of traffic sign recognition in bad weather and offers voice-based instruction in many languages to increase road safety. Using a mix of state-of-the-art technologies, including YOLOv8 for real-time sign detection and the Google Translate API, which supports NLP tasks, this research offers a full solution. The model's remarkable precision and efficacy underscore its capacity to revolutionize traffic safety and furnish a more secure and expedient driving encounter. With the world moving towards more autonomous mobility, this study is laying the groundwork for safer and more effective driving in the future. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Source
Lecture Notes in Networks and Systems;Volume;1181;pp.425-436
Date
01-01-2025
Publisher
Springer Science and Business Media Deutschland GmbH
Subject
Google translation API; Inclement weather; Multiple languages; Road safety; Traffic laws; Traffic signs; Voice-based guidance; YOLOv8
Coverage
Krishnendhu K., Christ (Deemed to be) University, Bengaluru, India; Mathew N.E., Christ (Deemed to be) University, Bengaluru, India; Gunavathi R., Christ (Deemed to be) University, Bengaluru, India; Johnson A., Christ (Deemed to be) University, Bengaluru, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 23673370; ISBN: 978-981978860-6;
Format
online
Language
English
Type
Conference paper

Citation

Krishnendhu, K.; Mathew, Neha Elizabeth; Gunavathi, R.; Johnson, Amala, “Multilingual Voice-Assisted for Traffic Sign Detection and Classification in Adverse Weather Conditions,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25673.

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