Q-bear is a product designed as an assistant to support parents of newborns. It is designed using an 18-layer deep learning architecture and processes GPU pre-training mode through more than 10,000 rows of crying data from babies, and also combines pre-process algorithm technology. Q-bear can precisely identify four basic needs, such as being fussy, tired, hungry, and having a dirty/wet diaper. It also can do a pain analysis to track your baby’s physiological condition at any time.
For example, Q-bear will auto-play a lullaby and a patented womb sound and start the sleep aid light when it detects the “tired” message. Q-bear can track diaper inventory when it detects a “change diaper” message. Q-bear can also turn on nightlights using voice control, so parents no longer have to get flustered at midnight.
Furthermore, Q-bear provides pushmail to notify parents about every condition—whether it’s the baby crying, an abnormal indoor temperature or humidity reading, abnormal urine frequency, or an abnormal pain index—all of that information will auto-notify and the data will be saved in Q-bear’s data storage. Caregivers can use the app to save their baby’s information without worrying about any data breaches.
In addition, Q-bear has a learning function, which can further increase the accuracy with the number of uses. In addition to being the most accurate (95%) prediction product on the market, it is also the only AIoT with automatic detection, activation and recording.