Smart Glove Based Sign Language Recognition System of Malayalam Alphabets

This paper presents a Malayalam hand gesture recognition system designed to assist deaf and dumb individuals using Arduino Nano. The proposed system uses sensor data to capture and interpret specific hand gestures representing Malayalam alphabets or words. By utilizing the computational power of the Arduino Nano,the system converts hand gestures into both text and audio outputs. This enables more effective communication for individuals with speech and hearing impairments, providing them with a cost-effective, portable, and user-friendly solution. The system is especially relevant for regions where Malayalam is predominantly spoken, offering inclusivity in local communities.This research highlights the potential of affordable embedded systems in the development of assistive technology, catering to regional languages and ensuring accessibility for differently-abled individuals.

Authors

Publication Details

Published
2025-04-03
DOI
https://doi.org/10.1109/ictest64710.2025.11042748
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Glove Based Sign Language Recognition System of Malayalam Alphabets

Shelda Sajeev, G. Chandran, Sachin Lal, Dhanush Kodi R et al.
Hand Gesture Recognition Systems
article

Smart Glove Based Sign Language Recognition System of Malayalam Alphabets

Shelda Sajeev, G. Chandran, Sachin Lal, Dhanush Kodi R, Joel Shaju, Nayana P. K
article en

Abstract

This paper presents a Malayalam hand gesture recognition system designed to assist deaf and dumb individuals using Arduino Nano. The proposed system uses sensor data to capture and interpret specific hand gestures representing Malayalam alphabets or words. By utilizing the computational power of the Arduino Nano,the system converts hand gestures into both text and audio outputs. This enables more effective communication for individuals with speech and hearing impairments, providing them with a cost-effective, portable, and user-friendly solution. The system is especially relevant for regions where Malayalam is predominantly spoken, offering inclusivity in local communities.This research highlights the potential of affordable embedded systems in the development of assistive technology, catering to regional languages and ensuring accessibility for differently-abled individuals.

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Openalex Percentile: Top 86%
Hand Gesture Recognition Systems
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