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Learning Human Routines (B/M/L)

Status: Offen

The amount of data that can be harvested from mobile phones is amazing: the way someone holds a phone, who they call, where they go, etc. All without requiring any input from the users themselves. We have an infrastructure to collect mobile phone sensor data. The goal of this project is to select a behavior of interest, learn that behavior through data collection from some number of smart phone users, and then use that behavior in an interesting application. For example, we have used information on when and how people charge their phones to identify when to perform network- or computation-heavy tasks without affecting battery life; we have used movement data of individuals to determine when a phone has likely been lost or stolen.

Contact: Prof. Anind Dey (

Contact/Ansprechpartner: Prof. Anind Dey

ETH ZurichDistributed Systems Group
Last updated August 15 2012 11:58:19 AM MET webvs