Developer Caleb Olson has upgraded a regular webcam with machine learning. The new device is able to recognize signs of hunger in the baby by identifying characteristic body movements.
Usually newborns cry when they want to eat. When hunger strikes, they begin to cry. Olson was tired of sleepless nights and decided to create a device that would warn of impending crying.
For his development, the man improved the webcam using the Google MediaPipe machine learning platform. During operation, the camera registers characteristic patterns of behavior, including smacking, nipple rejection, characteristic head movements in search of food, moving fists to the mouth. Olson assigned a certain score to each movement, depending on the degree of importance. Upon reaching a certain amount of points, a notification was received on the man’s smartphone that the baby should be fed.
Of course, the system still needs to be finalized, but with its help, Olson and his wife were certainly able to get more time to sleep and rest.
Usually newborns cry when they want to eat. When hunger strikes, they begin to cry. Olson was tired of sleepless nights and decided to create a device that would warn of impending crying.
For his development, the man improved the webcam using the Google MediaPipe machine learning platform. During operation, the camera registers characteristic patterns of behavior, including smacking, nipple rejection, characteristic head movements in search of food, moving fists to the mouth. Olson assigned a certain score to each movement, depending on the degree of importance. Upon reaching a certain amount of points, a notification was received on the man’s smartphone that the baby should be fed.
Of course, the system still needs to be finalized, but with its help, Olson and his wife were certainly able to get more time to sleep and rest.
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