Inspiration:
As students we have personally experienced the hardships and stresses that are brought upon us through sleep deprivation and insomnia. As a generation, visual light stimuli surround our every moment and as a highly influencing factor in sleep hygiene can be a important determinant in how we sleep. Having a centralised connected system of monitors that we would have around us everyday anyways would allow easy tracking of our sleep patterns and sleep hygiene behaviours.
How it works:
Before people actually go to sleep, they would put down their phones and charge their Apple Watch (if they have one). First thing they do after they wake up is often checking their phones and putting on their watches. Therefore, we believe that the usages of phone and watch are good indicators of the user’s sleeping pattern.
After obtaining data from Apple Health App (collected over iPhone and Apple Watch), we analyse the sleeping and wake up time of the user. We also collect data over Adafruit RGB Sensor TCS34725, from which we detect the light intensity of user’s bedroom.
All data is visualized in a desktop application using graphs, allowing users to understand more about their sleeping conditions.
What it does:
It provides an ecosystem of information that gives direct feedback to the users/patients as well as healthcare provides in the hopes of tracking sleep behaviours more accurately and conveniently. The combination of surrounding light intensity, mobile phone use, and etcetera will allow for a more complete picture of the quality of the users' sleep hygiene behaviours
Challenges:
The most difficult challenge that we faced was receiving the data sent from the sensor device through the cloud IoT set up with Microsoft Azure.
Accomplishments
We have managed to get the data output from both the RGB sensor about the light information and the iPhone Health App data that we can interpret as some of the main determining factors that indicate the time of the falling asleep and waking up time.
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