3 Juan Ye Susan McKeever Lorcan Coyle Steve Neely Simon Dobson 2008 ICPS '08: Proceedings of the 5th international conference on Pervasive services Sorrento, Italy ACM 131-140 06/07/2008 bayes networks, uncertainty, context, context awareness Pervasive computing is typically highly sensor-driven, but sensors provide only evidence of fact rather than facts themselves. The uncertainty of sensor data will affect each component in a pervasive computing system, which may decrease the quality of its provided services. We provide a general model to represent semantics of uncertainty in different levels (e.g., sensor, lower-level context and higher-level context). Within our model, fine-grained approaches are applied to evaluate and propagate uncertainties. They will help to resolve the uncertainty in each process of context management so that the effect of uncertainty on system services will be minimised.