LUNA: Bridging communication with sign language translation

This paper presents Learn, Unite, Network and Assist (LUNA) App, an assistive Internet of Things (IoT) system designed to facilitate two-way communication between individuals with hearing and speech impairments and the general public. The LUNA system integrates a smart glove embedded with flex sensors and an MPU6050 accelerometer to recognize hand gestures and translate them into real-time text displayed via a mobile application developed using Flutter. Beyond gesture recognition, LUNA includes a sign language learning module, GPS-based emergency location tracking, and video call functionality via WebRTC, enabling enhanced communication and user safety. Developed using the Scrum methodology, the system combines ESP32 microcontroller-based hardware with Firebase for real-time data handling. Experimental results demonstrate that LUNA achieves high accuracy and responsiveness, with gesture recognition response times ranging from 850 to 1200 milliseconds. This project represents a step toward inclusive communication by promoting mutual understanding and interaction between the disabled and non-disabled communities.

Publication Details

Journal
The International Islamic University Malaysia Repository (The International Islamic University Malaysia)
Published
2025-07-30
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
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article

LUNA: Bridging communication with sign language translation

The International Islamic University Malaysia Repository (The International Islamic University Malaysia)
Cell Image Analysis Techniques
article

LUNA: Bridging communication with sign language translation

article en

Abstract

This paper presents Learn, Unite, Network and Assist (LUNA) App, an assistive Internet of Things (IoT) system designed to facilitate two-way communication between individuals with hearing and speech impairments and the general public. The LUNA system integrates a smart glove embedded with flex sensors and an MPU6050 accelerometer to recognize hand gestures and translate them into real-time text displayed via a mobile application developed using Flutter. Beyond gesture recognition, LUNA includes a sign language learning module, GPS-based emergency location tracking, and video call functionality via WebRTC, enabling enhanced communication and user safety. Developed using the Scrum methodology, the system combines ESP32 microcontroller-based hardware with Firebase for real-time data handling. Experimental results demonstrate that LUNA achieves high accuracy and responsiveness, with gesture recognition response times ranging from 850 to 1200 milliseconds. This project represents a step toward inclusive communication by promoting mutual understanding and interaction between the disabled and non-disabled communities.

The International Islamic University Malaysia Repository (The International Islamic University Malaysia)
Quality Education
Openalex Percentile: Top 41%
Cell Image Analysis Techniques
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