N. Mostofa, K. Fullin, S. Zehtabian, S. S. Bacanli, L. Bölöni, and D. Turgut

IoT-Enabled Smart Mobility Devices for Aging and Rehabilitation


Cite as:

N. Mostofa, K. Fullin, S. Zehtabian, S. S. Bacanli, L. Bölöni, and D. Turgut. IoT-Enabled Smart Mobility Devices for Aging and Rehabilitation. In Proc. of IEEE International Conference on Communications (ICC-2020), pp. 1–6, June 2020.

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Abstract:

Elderly individuals often develop disabilities and require the aid of devices in order to perform everyday tasks. Specifically, elderly visually impaired individuals will need to use conventional aids, such as walkers or canes in order to navigate their surroundings. However, in a complex, unfamiliar environment, these devices won't be useful in avoiding obstacles. In this paper, we propose a smart walker that is augmented with an ultrasonic sensor and Google's TensorFlow framework that will detect and classify obstacles in the user's path and return information about the distance of that obstacle. The smart walker will also guide the user to the best possible path that will avoid these obstacles. The information will be conveyed through an audio and haptic interface. Our design will help users navigate their environment faster, safer, and easier than before.

BibTeX:

@inproceedings{Mostofa-2020-ICC,
	author = "N. Mostofa and K. Fullin and S. Zehtabian and S. S. Bacanli and L. B{\"o}l{\"o}ni and D. Turgut",
	title = "IoT-Enabled Smart Mobility Devices for Aging and Rehabilitation",
	booktitle = "Proc. of IEEE International Conference on Communications (ICC-2020)",
	year = "2020",
	month = "June",
  doi = "10.1109/ICC40277.2020.9149442",
  pages = "1-6",
	abstract = {
  Elderly individuals often develop disabilities and require the aid of devices in order to perform everyday tasks.  Specifically, elderly visually impaired individuals will need to use conventional aids, such as walkers or canes in order to navigate their surroundings.  However, in a complex, unfamiliar environment, these devices won't be useful in avoiding obstacles.  In this paper, we propose a smart walker that is augmented with an ultrasonic sensor and Google's TensorFlow framework that will detect and classify obstacles in the user's path and return information about the distance of that obstacle. The smart walker will also guide the user to the best possible path that will avoid these obstacles.  The information will be conveyed through an audio and haptic interface. Our design will help users navigate their environment faster, safer, and easier than before.
   },
}

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