Mostrar el registro sencillo del ítem
Artículo
A Context-Aware Artificial Intelligence-based System to Support Street Crossings For Pedestrians with Visual Impairments
dc.creator | Montanha, Aleksandro | es |
dc.creator | Oprescu, Andreea M. | es |
dc.creator | Romero Ternero, María del Carmen | es |
dc.date.accessioned | 2023-01-16T15:16:07Z | |
dc.date.available | 2023-01-16T15:16:07Z | |
dc.date.issued | 2022-04 | |
dc.identifier.citation | Montanha, A., Oprescu, A. . y Romero Ternero, M.d.C. (2022). A Context-Aware Artificial Intelligence-based System to Support Street Crossings For Pedestrians with Visual Impairments. Applied Artificial Intelligence, 36 (1). https://doi.org/10.1080/08839514.2022.2062818. | |
dc.identifier.issn | 0883-9514 | es |
dc.identifier.issn | 1087-6545 | es |
dc.identifier.uri | https://hdl.handle.net/11441/141400 | |
dc.description.abstract | Artificial intelligence has the potential to support and improve the quality of life of people with disabilities. Mobility is a potentially dangerous activity for people with impaired ability. This article presents an assistive technology solution to assist visually impaired pedestrians in safely crossing the street. We use a signal trilateration technique and deep learning (DL) for image processing to segment visually impaired pedestrians from the rest of pedestrians. The system receives information about the presence of a potential user through WiFi signals from a mobile application installed on the user’s phone. The software runs on an intelligent semaphore originally designed and installed to improve urban mobility in a smart city context. This solution can communicate with users, interpret the traffic situation, and make the necessary adjustments (with the semaphore’s capabilities) to ensure a safe street crossing. The proposed system has been implemented in Maringá, Brazil, for a one-year period. Trial tests carried out with visually impaired pedestrians confirm its feasibility and practicality in a real-life environment. | es |
dc.format | application/pdf | es |
dc.format.extent | 18 p. | es |
dc.language.iso | eng | es |
dc.publisher | Taylor and Francis | es |
dc.relation.ispartof | Applied Artificial Intelligence, 36 (1). | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | A Context-Aware Artificial Intelligence-based System to Support Street Crossings For Pedestrians with Visual Impairments | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Tecnología Electrónica | es |
dc.relation.publisherversion | https://www.tandfonline.com/doi/full/10.1080/08839514.2022.2062818 | es |
dc.identifier.doi | 10.1080/08839514.2022.2062818 | es |
dc.contributor.group | Universidad de Sevilla. TIC150: Tecnología Electrónica e Informática Industrial | es |
dc.journaltitle | Applied Artificial Intelligence | es |
dc.publication.volumen | 36 | es |
dc.publication.issue | 1 | es |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
AAI_romero-ternero_2022_context.pdf | 4.057Mb | ![]() | Ver/ | |