Evaluation of the Influence of Time Synchronisation on Classification Learning Based Movement Detection with Accelerometers

Context awareness is an important enabler of future applications in ubiquitous environments and has the potential to free the user from the control loop in a situation where he faces ever more connected devices. The context of a user can be accessed using data gathered from the user's personal devices and devices in his proximity. In this paper we examine the relation between time synchronisation of devices and context reasoning accuracy. For an application where we detect different activities of an office worker from acceleration data measured at the wrists, we show that insufficient time synchronisation leads to a significant decrease of reasoning accuracy. We show this for six commonly used classification learning algorithms that otherwise offer high accuracy provided devices are time synchronised. We also analyse the reasons that causes a lack of time synchronisation and why known synchronisation protocols are not applicable in ubiquitous environments. To solve the problems imposed by insufficient time synchronisation we propose a conceptual change in the communication paradigm used in architectures for context awareness.