Long periods spent in front of a screen are bad for the health. As you may know , your eyes are becoming tired and your visual acuity is damaged? That's why a programm should help to regulate the use of the screen in order to preserve the user's health.
The concept of the app is inspired by the adaptive brightness of screens.
But this time it uses AI and machine learning since your computer will analyze your degree of tireness through the webcam of your computer.
Then it will adapt the brightness taking in account your level of shape.
Adaptive Brightness can actually do more than changing the luminosity.It can indeed turn on the blue light filter and give you some tips (have a break for instance).
If a user works for 2 hours straight (or even more) without showing evidence of tireness , the user will be advised to reudce luminosity and turning on blue light fighter but it would not be done automatically.
To do this , the programm will analyze thanks to AI your face through the webcam (or the camera if you are using a smartphone, of course it is more useful on computers). It will take in account your mood , the number of times you're yawning , if you are rubbing your eyes and others similar signs of tireness.
The camera will read the expressions on your face and interpret it as a sign or not of tireness and adapting luminosity. The AI keeps information of your faces and adjusts the settings of the screen depending on your behaviour.
Some gestures like that above are detected and if the are repeated several times you computer will thus act by itself.
Here is a short ml5.js tutorial. It explains how to use AI and machine learning and more precisely in the case of image classification.
Here is a more accurate explanation of the functionment of Mobile
Net. Yhanks to this technology , faces will be first analyzed through Feature Learning.
MobileNet can recognize images in two ways :uploaded images and images in real time with camera.