Towards a Context-Aware Personal Scheduler

Towards a Context-Aware Personal Scheduler,Nathan Norton,Samsung Lim

Towards a Context-Aware Personal Scheduler  
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Modern mobile devices have features that are now starting to enable them for uses not even considered feasible as recent as 5 years ago. Mobile devices are now being used to obtain context to events, taking in current location and using this data to perform computations. This paper describes the design of a context-aware location-based personal information manager. This type of a new information manager takes factors such as location, current context, and other tasks due, in order to provide users with input on an optimal ordering of events. The process of deciding which task to take involves breaking tasks down into their relationships based on urgency to complete, priority and location amongst other factors. A prototype application developed in this study shows that it is feasible to organize a to- do list that can incorporate location into its schedule without too much of a detrimental effect on a mobile device's battery performance. On a more general level it is also possible to place any number of tasks and their attributes into a list and get a scheduler to smartly choose a natural ordering for these. If we treat each independent variable as a dimension in an n- dimensional Euclidean space we can use distances to generate an overall order of these tasks. Ordering and normalizing the data is an area that needs to be looked at more closely in order to fully identify what the best way to go forward is. Should we increase the range of normalized values? Or should we change the weights of other given values so that tasks further away are given an even lower (or higher) score? These are the questions that could be posed in order to improve the ordering scheme we devised.
Published in 2010.
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