Smart Gloves Technology for Sign Language Translation: Enhancing Communication Accessibility

Imagine a world where hands-on communication replaces spoken words, fostering hearing-deaf communication. Smart gloves are transforming accessibility and sign language translation. These advanced gloves identify complicated handwriting and sign language gestures in real time using several sensors and machine learning algorithms. After that, advanced algorithms translate the gestures into spoken or written words, enabling hearing individuals to converse with deaf people. Smart gloves identify and understand hand gestures, helping deaf and mute persons communicate in real life. Smart sign language gloves use sensor technology and machine learning to improve communication. Flex sensors measure finger bending, accelerometers and gyroscopes hand orientation, and touch sensors finger placement. Glove micro controllers handle sensor data in real time. Recurrent neural networks (RNNs) or long short-term memory (LSTM) networks read gesture input and convert it into text or voice. High accuracy across sign language dialects, low latency for real-time translation, and comfortable, inconspicuous gloves are key hurdles. Recent advances include deep learning gesture detection accuracy, battery longevity, and haptic feedback for two-way communication. This technique may improve communication accessibility in virtual reality interfaces, human-computer interaction, and deaf and hard of hearing.