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Volume 12, Issue 4 (April 2026)

Gesture-controlled Smart Glove With Voice Assistance And Alert System

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7.883
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Volume 12 Issue 07

July 2026

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Author(s)

Kalidhas K Leha Sri G Naveen Kumar C Pratheksha Sri T T Ruban Raj M

Abstract

Communication Remains A Fundamental Human Need, Yet Individuals With Hearing And Speech Impairments Face Persistent Barriers In Daily Interactions. Traditional Methods Like Sign Language Require Mutual Proficiency Between Participants, Limiting Effectiveness In Diverse Real- World Scenarios Where Hearing Individuals Lack Sign Language Knowledge. This Paper Proposes An Innovative, Affordable Wearable Communication Aid Designed As A Smart Glove To Bridge This Gap, Enabling Seamless Two-way Interaction For Disabled Users. The System Integrates Tilt Sensors Within A Comfortable Wearable Glove To Precisely Detect Finger Gestures And Hand Positions. These Gestures Map To A Library Of Predefined Messages (e.g., "Help," "Water," "Thank You") Processed By An ESP32 Microcontroller. Using User Datagram Protocol (UDP) For Low-latency Wireless Transmission, Detected Messages Instantly Appear As Text Or Speech Output On Connected Smartphones, Tablets, Or Dedicated Displays. This Facilitates Rapid, Reliable Communication With Hearing Individuals In Real-time Settings Such As Shopping, Medical Visits, Or Public Spaces. Complementing Gesture Input, The System Incorporates Speech-to-text Conversion, Capturing Nearby Spoken Language And Displaying It As Readable Text On The User's Device. This Bidirectional Functionality Supports Comprehensive Conversations, Breaking Traditional One-way Communication Limitations. The Design Prioritizes Portability (lightweight Glove Form-factor), Low Power Consumption For All-day Use, Intuitive Gesture Mapping For Quick Learning, And Real-time Responsiveness (<100ms Latency). By Combining Embedded Gesture Recognition With Modern Wireless Protocols, This Assistive Technology Enhances User Independence, Boosts Social Participation, And Reduces Isolation. Cost-effective Components Ensure Accessibility Across Socioeconomic Groups, While Modular Design Supports Future Enhancements Like AI Gesture Learning And Multi-language Support. This Solution Advances Wearable Assistive Technology, Promoting Inclusivity And Equal Communication Opportunities.


Keywords

Gesture Recognition ESP32 Wearable Assistive Technology Tilt Sensors UDP Communication Speech-to-text.

Paper ID

IJSARTV12I4105030

Publication Date

April 16, 2026

Research Area

Electronics And Communication Engineering

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