A multi-DL fuzzy approach to image recognition for a real-time traffic alert system
| Title: | A multi-DL fuzzy approach to image recognition for a real-time traffic alert system |
|---|---|
| Authors: | Muñoz, Andrés, Martínez-España, Raquel, Guerrero-Contreras, Gabriel, Balderas-Díaz, Sara, Arcas-Túnez, Francisco, Bueno-Crespo, Andrés |
| Source: | Journal of Ambient Intelligence and Smart Environments; February 2025, Vol. 17 Issue: 1 p101-116, 16p |
| Abstract: | This paper presents a novel Multi-DL Fuzzy Approach aimed at performing image recognition in the development of a real-time traffic alert system, addressing the problem of traffic congestion and related incidents. Traditional monitoring by road operators predominantly relies on fixed location cameras, yielding limited and sometimes ambiguous information. This study proposes leveraging Twitter (now known as ‘X’) as a more comprehensive data source alongside employing fuzzy techniques with Deep Learning (DL) neural networks such as CNN, VGG16, and Xception to analyze and classify traffic images. The innovative integration of these technologies augments the precision in categorizing varying traffic conditions, namely fluid and dense traffic, accidents and fires. Thus, this proposal mitigates the ambiguities prevalent in traffic image interpretation, and reduces the dependency on static data sources. The proposed models showed improved results by combining information from the DL models, elevating accuracy from 84% in crisp classification to 90% utilizing fuzzy information. |
| Database: | Supplemental Index |
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| Items | – Name: Title Label: Title Group: Ti Data: A multi-DL fuzzy approach to image recognition for a real-time traffic alert system – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Muñoz%2C+Andrés%22">Muñoz, Andrés</searchLink><br /><searchLink fieldCode="AR" term="%22Martínez-España%2C+Raquel%22">Martínez-España, Raquel</searchLink><br /><searchLink fieldCode="AR" term="%22Guerrero-Contreras%2C+Gabriel%22">Guerrero-Contreras, Gabriel</searchLink><br /><searchLink fieldCode="AR" term="%22Balderas-Díaz%2C+Sara%22">Balderas-Díaz, Sara</searchLink><br /><searchLink fieldCode="AR" term="%22Arcas-Túnez%2C+Francisco%22">Arcas-Túnez, Francisco</searchLink><br /><searchLink fieldCode="AR" term="%22Bueno-Crespo%2C+Andrés%22">Bueno-Crespo, Andrés</searchLink> – Name: TitleSource Label: Source Group: Src Data: Journal of Ambient Intelligence and Smart Environments; February 2025, Vol. 17 Issue: 1 p101-116, 16p – Name: Abstract Label: Abstract Group: Ab Data: This paper presents a novel Multi-DL Fuzzy Approach aimed at performing image recognition in the development of a real-time traffic alert system, addressing the problem of traffic congestion and related incidents. Traditional monitoring by road operators predominantly relies on fixed location cameras, yielding limited and sometimes ambiguous information. This study proposes leveraging Twitter (now known as ‘X’) as a more comprehensive data source alongside employing fuzzy techniques with Deep Learning (DL) neural networks such as CNN, VGG16, and Xception to analyze and classify traffic images. The innovative integration of these technologies augments the precision in categorizing varying traffic conditions, namely fluid and dense traffic, accidents and fires. Thus, this proposal mitigates the ambiguities prevalent in traffic image interpretation, and reduces the dependency on static data sources. The proposed models showed improved results by combining information from the DL models, elevating accuracy from 84% in crisp classification to 90% utilizing fuzzy information. |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3233/AIS-230433 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 101 Titles: – TitleFull: A multi-DL fuzzy approach to image recognition for a real-time traffic alert system Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Muñoz, Andrés – PersonEntity: Name: NameFull: Martínez-España, Raquel – PersonEntity: Name: NameFull: Guerrero-Contreras, Gabriel – PersonEntity: Name: NameFull: Balderas-Díaz, Sara – PersonEntity: Name: NameFull: Arcas-Túnez, Francisco – PersonEntity: Name: NameFull: Bueno-Crespo, Andrés IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: February 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 18761364 – Type: issn-print Value: 18761372 Numbering: – Type: volume Value: 17 – Type: issue Value: 1 Titles: – TitleFull: Journal of Ambient Intelligence and Smart Environments Type: main |
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