Practical Activity Recognition using GSM Data

The ability to provide context aware behaviour on a cell phone such as whether a user is walking or driving has previously only been possible via the use of additional hardware sensors such as an accelerometer. In this paper we demonstrate how a level of context awareness similar to that achieved with an accelerometer can be obtained using information readily available on a typical GSM cell phone. We show that by using the patterns of signal strength fluctuations and changes to the current serving cell and monitored neighbouring cells it is possible to distinguish between various states of movement such as walking, driving in a motor car and remaining stationary. We demonstrate how the calibration of the cell phone for use in a given environment can be implemented in an automatic and unsupervised manner, and that we can achieve a classification accuracy of around 80%.