The next evolution of loT on your wrist
Today's IoT, predominantly used in homes and commanded by voice assistants, needs a more seamless, effortless, and efficient control mechanism. Exploring from non-speech sound recognition and gesture control, we aim to enhance user interaction with IoT devices. Our machine learning model identifies user activities from environmental sounds, enabling swift IoT control through wearables. Our ultimate goal is to develop a superior model promoting a more streamlined and intuitive IoT experience.
Sunzhe (Selvin) Yang
Zhongyue (Sherley) Zhang