Machine Learning and Location Fingerprinting to Improve UX in a Ubiquitous Application
GREatPrint is a ubiquitous application that prints documents from mobile devices to the closest printer to the user at the GREat research lab. The first version of the application (GREatPrint V1) was evaluated and showed a low accuracy in the detection of the closest printer. In order to improve the application, this study proposes a new version of GREatPrint (GREatPrint V2) based on a machine learning algorithm and location fingerprinting technique. Therefore, this paper describes GREatPrint V2 with the approach used to improve its context-awareness. Also, it presents results from a case study performed to evaluate the user interaction quality through software quality measures for ubiquitous systems.
KeywordsUbiquitous application RSSI Fingerprinting Machine learning User experience Context-awareness Calmness
We would like to thank the CTQS/GREat team for the technical support for this work and also to the CAcTUS - ContextAwareness Testing for Ubiquitous Systems project supported by CNPq (MCT/CNPq 14/2013 - Universal) under grant number 484380/2013-3.
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