Enhancing accessibility and inclusivity for people with disabilities

Registration ID: IJNRD_217171

Published ID: IJNRD2404130

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Niveditha P, Pooja D, Dr.Susila sakthy

Machine Learning, Home Appliances, Computer Vision, Gesture Recognition, Convolutional neural network, Alert messages.

This study introduces a new method of home automation tailored to the needs of those who have trouble moving about. Using only your hands, you can turn on and off lights, fans, and other electrical devices. Providing individuals with mobility impairments with the means to autonomously manage their living area is the declared goal of the initiative, which aims to encourage greater independence and better their quality of life. The suggested system uses computer vision and machine learning techniques to decipher recorded hand motions seen through a camera interface. The system may be able to interpret specific hand movements as commands to operate different home appliances if it has learned to recognize them. We create and deploy a reliable system for the detection and categorization of gestures in real-time. Modern computer vision techniques, including Convolutional Neural Networks (CNNs) and algorithms for hand tracking, enable the system to accurately understand motion. Assigning certain commands to the recognized motions allows for the operation of smart home electrical products, such as lighting and ceiling fans. Plus, if the disabled person needs assistance, this device may notify the caregiver. We aim to enable people with impairments to live more independently and comfortably in their homes by giving this home automation system that is controlled by gestures. Accessibility and inclusion in smart home settings are significantly advanced by our effort, which leverages state-of-the-art technology and prioritizes user-centric design concepts.

Published Paper   E-Certificate

Niveditha P, Pooja D, & Dr.Susila sakthy (April-2024). Enhancing accessibility and inclusivity for people with disabilities . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), b232-b237. https://ijnrd.org/papers/IJNRD2404130.pdf

Volume 9 Issue 4, April-2024

Pages : b232-b237

Paper Reg. ID: IJNRD_217171

Published Paper Id: IJNRD2404130

Downloads: 000122061

Research Area: Information Technology 

Author Type: Indian Author

Country: Chennai, Tamilnadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404130.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404130

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