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IoT-based Smart Home Automation Using Gesture Control and Machine Learning for Individuals with Auditory Challenges
Research Article | Published: 19 November 2024
IECE Transactions on Internet of Things Volume 2, Issue 4, 2024: 74-82
Volume 2, Issue 4, IECE Transactions on Internet of Things
Volume 2, Issue 4, 2024
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Jinchao Chen
Jinchao Chen
Northwestern Polytechnical University, China
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IECE Transactions on Internet of Things, Volume 2, Issue 4, 2024: 74-82

Free to Read | Research Article | 19 November 2024
IoT-based Smart Home Automation Using Gesture Control and Machine Learning for Individuals with Auditory Challenges
by
Baleegha Fatima Baleegha Fatima 1
Bilal Mushtaq Bilal Mushtaq 1 *
Muhammad Ammar Iqbal Muhammad Ammar Iqbal 1
Abbas Ahmed Abbas Ahmed 1
1 Beaconhouse International College, Islamabad, Pakistan
* Corresponding Author: Bilal Mushtaq, [email protected]
DOI: 10.62762/TIOT.2024.723193
Received: 02 September 2024, Accepted: 04 November 2024, Published: 19 November 2024  
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Abstract
This paper reviews advancements in assistive technology for deaf and hard of hearing individuals, highlighting the Internet of Things' (IoTs) pivotal role in enhancing their daily lives. Despite progress in sign language technologies, communication barriers persist. To address these gaps, we developed a video-based American Sign Language (ASL) identification system. Our approach utilizes MediaPipe for hand tracking, OpenCV for image normalization, and Gesture Control Convolutional Neural Network (CNN) for gesture localization. Implemented in Python, the system records video streams, filters hand regions, and recognizes ASL letter gestures with high accuracy. Leveraging computer vision and machine learning, our system enhances user experience, breaks communication barriers, promotes inclusivity, and supports accessible technologies. This innovative solution empowers deaf and hard of hearing individuals to fully participate in their communities, contributing to a more inclusive and accessible environment.
Graphical Abstract
IoT-based Smart Home Automation Using Gesture Control and Machine Learning for Individuals with Auditory Challenges
Keywords
convolutional neural networks
sign language
artificial intelligence
machine learning
American sign language
image processing
internet of things
home automation
Funding
This work was supported without any funding.
References
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Cite This Article
APA Style
Fatima, B., Mushtaq, B., Iqbal, M. A., & Ahmed, A. (2024). IoT-based Smart Home Automation Using Gesture Control and Machine Learning for Individuals with Auditory Challenges. IECE Transactions on Internet of Things, 2(4), 74–82. https://doi.org/10.62762/TIOT.2024.723193
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