With sensors and computers becoming portable, and even wearable, people are now able to get to know themselves better by measuring themselves. Lifelogging or Quantified Self is steadily becoming a global movement, with people tracking (and often sharing) various aspects of their lives, each for their own reasons.

Lifeloggers have been known to track their bodily functions, weight, food consumption, movements, location, sport acvitity, sleep patterns or even the number of needles knitted per day. These datasets can be valuable tool for changing and improving their lives. Immediate feedback loops and long-term patterns people the insight they need to adjust their behaviour.

CommonSense is the perfect tool for lifeloggers, as it allows them to connect any sensor they like, and visualize data in real-time. Any information that can be measured by a sensor, can be processed in CommonSense.

By using CommonSense's standard learning algorithms, or by adding their own, users can let CommonSense interpret their data for them, and learn to recognize patterns and deviations.