The global prevalence of visual disabilities is increasing, significantly impacting the quality of life and social inclusion of those affected. Existing technologies, while helpful, continue to face challenges in terms of cost, accessibility, and real-time effectiveness. Individuals with visual impairments face significant barriers in their daily interactions with the environment, limiting their independence and social participation. The lack of adaptable and personalized solutions that address these specific needs remains a significant barrier. This study presents an extension of the Modeling Scenarios of the Internet of Things (MoSIoT) framework, a platform designed to improve the quality of life of people with disabilities by enhancing their interactions with IoT devices. The enhanced MoSIoT framework uses artificial intelligence and augmented reality technologies to significantly improve navigation and environmental interaction, enhancing the well-being of individuals with visual impairments. The proposed enhancements include advanced object detection, scene recognition, and augmented reality geolocation, all tailored to provide a richer and more autonomous user experience. A case study conducted as part of this research illustrates the practical application of these technologies in a real-world scenario, demonstrating how they can be used to support individuals with visual impairments in various everyday contexts. Practical tests conducted using tools such as YOLO for object recognition and Azure IoT for device integration have significantly improved user autonomy and quality of life. The results show that the enhanced framework can facilitate more effective environmental interaction and better social inclusion, highlighting its potential for implementation across different contexts and devices.

Enhancing the well-being of individuals with vision impairments: a comprehensive examination of the MoSIoT framework

Leporini, Barbara;
2026-01-01

Abstract

The global prevalence of visual disabilities is increasing, significantly impacting the quality of life and social inclusion of those affected. Existing technologies, while helpful, continue to face challenges in terms of cost, accessibility, and real-time effectiveness. Individuals with visual impairments face significant barriers in their daily interactions with the environment, limiting their independence and social participation. The lack of adaptable and personalized solutions that address these specific needs remains a significant barrier. This study presents an extension of the Modeling Scenarios of the Internet of Things (MoSIoT) framework, a platform designed to improve the quality of life of people with disabilities by enhancing their interactions with IoT devices. The enhanced MoSIoT framework uses artificial intelligence and augmented reality technologies to significantly improve navigation and environmental interaction, enhancing the well-being of individuals with visual impairments. The proposed enhancements include advanced object detection, scene recognition, and augmented reality geolocation, all tailored to provide a richer and more autonomous user experience. A case study conducted as part of this research illustrates the practical application of these technologies in a real-world scenario, demonstrating how they can be used to support individuals with visual impairments in various everyday contexts. Practical tests conducted using tools such as YOLO for object recognition and Azure IoT for device integration have significantly improved user autonomy and quality of life. The results show that the enhanced framework can facilitate more effective environmental interaction and better social inclusion, highlighting its potential for implementation across different contexts and devices.
2026
Nasabeh, Shahab; Meliá, Santiago; Leporini, Barbara; Gadzhimusieva, Diana
File in questo prodotto:
File Dimensione Formato  
s10209-026-01363-2.pdf

accesso aperto

Tipologia: Versione finale editoriale
Licenza: Creative commons
Dimensione 4.29 MB
Formato Adobe PDF
4.29 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1364848
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact