  We introduce a system to measure individual happiness based on interpreting
body sensors on smartwatches. In our prototype system we use a Pebble
smartwatch to track activity, heartrate, light level, and GPS coordinates, and
extend it with external information such as weather data, humidity, and day of
the week. Training our machine learning-based mood prediction system using
random forests with data manually entered into the smartwatch, we achieve
prediction accuracy of up to 94%. We find that besides body signals, the
weather data exerts a strong influence on mood. In addition our system also
allows us to identify friends who are indicators of our positive or negative
mood.
