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Empowering the Disabled: Object Detection and Recognition for Enhanced Autonomy

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Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2024) (UCAmI 2024)

Abstract

The growing elderly population has led to an increase in individuals suffering some kind of disability. The integration of object detection and recognition technologies into assistive devices open new possibilities for improving the independence and safety of such people. In this context, we propose a novel help system, based on Google Glass and YOLO to facilitate the daily activities of those people who have problems recognizing objects and remembering what they are used for. For example, the glasses’ speaker system verbalizes the name of an object the user needs to identify and pick up from a table, and the device confirms the correct selection. Additionally, an assistive application is deployed to support daily activities, where the glasses explain the function of an object when the user requires assistance. This innovative approach not only enhances cognitive stimulation but also provides practical support, significantly improving the quality of life for those individuals. In this work we analyze (experimentally) two different versions of the help system and, we conclude that both provide a good performance in terms of latency and reliability.

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Acknowledgements

This work has been funded by the projects R+D+i PID2021-123278OB-I00 and PDC2022-133370-I00 from MCI-N/AEI/10.13039/501100011033/ and ERDF funds; and the Department of Informatics of the University of Almería. M. Lupión is a fellowship of the FPU program from the Spanish Ministry of Education (FPU19/02756).

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Lupión, M., Sanjuan, J., González-Ruiz, V., Ortigosa, P. (2024). Empowering the Disabled: Object Detection and Recognition for Enhanced Autonomy. In: Bravo, J., Nugent, C., Cleland, I. (eds) Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2024). UCAmI 2024. Lecture Notes in Networks and Systems, vol 1212. Springer, Cham. https://doi.org/10.1007/978-3-031-77571-0_27

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