Our exposure to light is universal, and so is our need for light. Light exposure directly affects our physical and mental states. Yet there is currently no way to track our exposure, as a precursor to optimizing it.
PHI-K allows us to track our light exposure over time and take suggestions to optimize it. The system comprises a wearable light-temperature sensor, a smartphone app to record the data and display suggestions, and an open system that communicates to third-party devices.
The sensor and app are distributed as a package. The sensor measures light temperature periodically throughout
the day, and synchronizes that data
to the user’s smartphone. Using a GPS location and the local weather forecast, the app estimates the light temperature outside.
An algorithm analyzes the difference between the measured and expected light temperatures and makes suggestions to optimize light exposure, based on
factors such as the magnitude of the difference, the duration of exposure to a given light temperature and the time
of day.
Users can also learn more about the science of light exposure and add devices – such as a light-therapy box – to
tailor and optimize the suggestions from the app.
We designed the phi-k system around three use cases:
novices, quantified-self (QS) enthusiasts, and those who
suffer from Circadian Rhythm Sleep Disorders (CRSD) and
related conditions.
We stratified the app to provide different data resolutions
for each of the three kinds of user. Novices require the most
qualitative data, such as a colour map over time, visually
showing the change in light temperature over the course of
the day. People with CRSDs require the most quantitative
data, to ensure that the phi-k system more precisely meets
their medical requirements, such as knowing specific light
temperature values at any time. The app begins with the
most qualitative data, and allows the user to drill into higher-resolution data.
