Solar-Powered Wheelchair with CNN-Based Gesture Control and Home Automation

This project is a groundbreaking advancement in assistive technology, specifically in the development of smart, solar-powered wheelchairs that enhance mobility, independence, and user comfort. By integrating cutting-edge technologies such as Convolutional Neural Networks (CNNs) for gesture control and smart home automation, this wheelchair surpasses conventional models, allowing seamless interaction with the surrounding environment. The core innovation lies in its gesture control interface, enabling users to maneuver the wheelchair effortlessly with or without head movement. CNNs play a crucial role in detecting and classifying gestures in real time through image and video processing, ensuring high responsiveness, accuracy, and reliability for an intuitive user experience. Additionally, the wheelchair incorporates home automation, allowing users to control essential devices like lights, fans, and smart locks directly from their seats, thereby reducing dependency on external assistance and enhancing personal independence. Furthermore, its reliance on solar power makes it an environmentally sustainable solution, minimizing energy consumption and promoting eco-friendliness. By combining advanced CNN-based gesture control, smart home automation, and solar energy, this innovative wheelchair not only enhances the quality of life for individuals with disabilities but also contributes to a more sustainable and inclusive future, empowering users with greater autonomy and ease in daily activities.

Authors

Publication Details

Journal
International Research Journal on Advanced Engineering Hub (IRJAEH)
Published
2025-04-16
DOI
https://doi.org/10.47392/irjaeh.2025.0192
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
0.00
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article

Solar-Powered Wheelchair with CNN-Based Gesture Control and Home Automation

D. Magdalin Mary, M. Monisha, Mahalakshmi Priya R, Anusha Aswath
1 links
International Research Journal on Advanced Engineering Hub (IRJAEH)
Gaze Tracking and Assistive Technology
article

Solar-Powered Wheelchair with CNN-Based Gesture Control and Home Automation

D. Magdalin Mary, M. Monisha, Mahalakshmi Priya R, Anusha Aswath
article en

Abstract

This project is a groundbreaking advancement in assistive technology, specifically in the development of smart, solar-powered wheelchairs that enhance mobility, independence, and user comfort. By integrating cutting-edge technologies such as Convolutional Neural Networks (CNNs) for gesture control and smart home automation, this wheelchair surpasses conventional models, allowing seamless interaction with the surrounding environment. The core innovation lies in its gesture control interface, enabling users to maneuver the wheelchair effortlessly with or without head movement. CNNs play a crucial role in detecting and classifying gestures in real time through image and video processing, ensuring high responsiveness, accuracy, and reliability for an intuitive user experience. Additionally, the wheelchair incorporates home automation, allowing users to control essential devices like lights, fans, and smart locks directly from their seats, thereby reducing dependency on external assistance and enhancing personal independence. Furthermore, its reliance on solar power makes it an environmentally sustainable solution, minimizing energy consumption and promoting eco-friendliness. By combining advanced CNN-based gesture control, smart home automation, and solar energy, this innovative wheelchair not only enhances the quality of life for individuals with disabilities but also contributes to a more sustainable and inclusive future, empowering users with greater autonomy and ease in daily activities.

International Research Journal on Advanced Engineering Hub (IRJAEH)Vol. 3(04)
Openalex Percentile: Top 92%
Gaze Tracking and Assistive Technology
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Solar-Powered Wheelchair with CNN-Based Gesture Control and Home Automation — D. Magdalin Mary, M. Monisha, et al. · International Research Journal on Advanced Engineering Hub (IRJAEH) (2025) | TGRS Research Map | TGRS