Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Krishnendhu, K.; Mathew, Neha Elizabeth; Gunavathi, R.; Johnson, Amala Title A name given to the resource Multilingual Voice-Assisted for Traffic Sign Detection and Classification in Adverse Weather Conditions Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1181;pp.425-436 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-97-8861-3_36" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-8861-3_36</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105000636106?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105000636106?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant 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 Description An account of the resource 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. Subject The topic of the resource Google translation API; Inclement weather; Multiple languages; Road safety; Traffic laws; Traffic signs; Voice-based guidance; YOLOv8 Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981978860-6; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online