IoT-Enabled Sign Language Interpreter Glove
K.R. Prabha, M Mahalingamuthuram., Chiwate Sheetal Mukesh, V.P Priya Dharshan · 2024
This research presents an innovative IoT-based sign language interpreter glove (IoT-SLIG) designed to facilitate communication for individuals with hearing impairments. By utilizing advanced sensor technology and machine learning, the IoT-SLIG accurately interprets hand movements and translates them into spoken audio, text, or haptic feedback. The IoT-SLIG incorporates a machine learning algorithm trained on a comprehensive dataset of sign language gestures. This algorithm processes sensor data from the glove and matches it to corresponding sign language movements, enabling real-time interpretation. The device offers versatility by accommodating various communication preferences and accessibility needs. User-centric features, such as customization options, adaptability to different sign language dialects, and continuous learning capabilities, enhance the IoT-SLIG’s usability and effectiveness. This technology has the potential to significantly improve communication for individuals with hearing impairments, fostering greater inclusion and accessibility.