IoT-Driven Smart Glasses for Visual Assistance in Elderly Care with Deep Learning Solutions

Smart glasses with advanced visual aid features are a primary instance of how recent advances in the IoT and machine learning have creative solutions for the care of the elderly. These Internet of Things (IoT) devices use machine learning methods, most especially Convolutional Neural Networks (CNNs), to help the elderly with a variety of tasks in real-time, thereby improving their quality of life. This research delves into incorporating CNN algorithms into IoT smart glasses, specifically examining features like object identification, text enlargement, and fall detection. It goes over the theoretical underpinnings of CNNs for image processing, how they may be personalized to meet the specific requirements of individual users, and how they facilitate telemedicine and remote healthcare monitoring. It also optimized the user interface and thought about optimized privacy and security to ensure it works in senior care settings. This investigation highlights the revolutionary effect that CNN-powered IoT smart glasses might have on the autonomy, security, and general well-being of the elderly. It also emphasizes the potential for their widespread use in healthcare transformation.

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Published
2025-04-24
DOI
https://doi.org/10.1109/amathe65477.2025.11081239
Citations
1
Primary Topic
Digital Media and Visual Art
Type
article
Field-Weighted Citation Impact
3.54
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IoT-Driven Smart Glasses for Visual Assistance in Elderly Care with Deep Learning Solutions

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IoT-Driven Smart Glasses for Visual Assistance in Elderly Care with Deep Learning Solutions

T. Geetha, N. Mohankumar, P. Sangeetha, D. Bharathi Dhasan, S. Murugan, Chitra Sabapathy Ranganathan
article en
1 citations

Abstract

Smart glasses with advanced visual aid features are a primary instance of how recent advances in the IoT and machine learning have creative solutions for the care of the elderly. These Internet of Things (IoT) devices use machine learning methods, most especially Convolutional Neural Networks (CNNs), to help the elderly with a variety of tasks in real-time, thereby improving their quality of life. This research delves into incorporating CNN algorithms into IoT smart glasses, specifically examining features like object identification, text enlargement, and fall detection. It goes over the theoretical underpinnings of CNNs for image processing, how they may be personalized to meet the specific requirements of individual users, and how they facilitate telemedicine and remote healthcare monitoring. It also optimized the user interface and thought about optimized privacy and security to ensure it works in senior care settings. This investigation highlights the revolutionary effect that CNN-powered IoT smart glasses might have on the autonomy, security, and general well-being of the elderly. It also emphasizes the potential for their widespread use in healthcare transformation.

Vinayaka Missions University (IN), Dr. M.G.R. Educational and Research Institute (IN), Symbiosis International University (IN), Saveetha University (IN)
Openalex Percentile: Top 8%
Digital Media and Visual Art
3.54
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