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Voice Controlled Wheelchair with Home Automation

by Shoeb Khan, Neamat Ansari, Md. Mudassir, Safi Nazimuddin, Geeta Desai
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 23
Year of Publication: 2024
Authors: Shoeb Khan, Neamat Ansari, Md. Mudassir, Safi Nazimuddin, Geeta Desai
10.5120/ijca2024923680

Shoeb Khan, Neamat Ansari, Md. Mudassir, Safi Nazimuddin, Geeta Desai . Voice Controlled Wheelchair with Home Automation. International Journal of Computer Applications. 186, 23 ( May 2024), 43-49. DOI=10.5120/ijca2024923680

@article{ 10.5120/ijca2024923680,
author = { Shoeb Khan, Neamat Ansari, Md. Mudassir, Safi Nazimuddin, Geeta Desai },
title = { Voice Controlled Wheelchair with Home Automation },
journal = { International Journal of Computer Applications },
issue_date = { May 2024 },
volume = { 186 },
number = { 23 },
month = { May },
year = { 2024 },
issn = { 0975-8887 },
pages = { 43-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number23/voice-controlled-wheelchair-with-home-automation/ },
doi = { 10.5120/ijca2024923680 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-05-31T22:32:03.069563+05:30
%A Shoeb Khan
%A Neamat Ansari
%A Md. Mudassir
%A Safi Nazimuddin
%A Geeta Desai
%T Voice Controlled Wheelchair with Home Automation
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 23
%P 43-49
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This research presents a novel voice-controlled wheelchair system that integrates with home automation technologies to enhance mobility and independence for individuals with disabilities. Through a multidisciplinary approach, this project addresses the limitations of existing assistive devices by leveraging state-of-the-art voice recognition and machine learning techniques. The primary objectives of this study were twofold: first, to develop a highly accurate and reliable voice controlled wheelchair system capable of interpreting user commands with precision. Second, to seamlessly integrate this system with home automation devices, enabling users to control their living environments through natural voice commands. The research methodology combines hardware design, software development, and machine learning algorithms. The results of this project demonstrate significant advancements in assistive technology, offering a comprehensive solution that empowers users with increased independence and an improved quality of life. The integration of voice control and home automation features represents an approach that holds broader implications for the fields of assistive technology and healthcare.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Voice-controlled wheelchair Speech recognition ESP32 CNN Home automation Obstacle detection

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