FlexLingo: Sign Language Translation
ArduinoFlex SensorsRandom ForestBiLSTMReact.jsExpress.jsMPU6050TensorflowKerasPythonIoTMLFinal Year Project4 Members TeamTeam Lead RoleWeb
An IoT-powered smart glove that translates sign language gestures into real-time text and speech. Built with Arduino and flex sensors, it uses a Random Forest model to achieve 95% gesture recognition accuracy, reducing latency to under 200ms. The system features a React.js frontend and Express.js backend, delivering seamless communication assistance.
Achievements
- Achieved 95% gesture recognition accuracy using Random Forest
- Outperformed BiLSTM model by 13%
- Reduced data processing latency to under 200ms
- Featured in college tech fest innovation showcase
