An Intelligent Notification System Using Context from Real-Time Self Activity Monitoring System
Keywords:
Notification system, context awareness, contexture modeling, user logging, moment prediction.Abstract
People can now receive custom-made information through Smartphones, tablets or wearable devices. However, people often tend to miss vital information, even reminders, in the flood of notifications. The problem of finding convenient moments for need-to-know information should be investigated. Because each person’s message awareness pattern on a smart medium might be different, the necessity of personalized notification time should be emphasized. We believe that tracking changes in a user’s physical activity and other contextual factors will reveal the most convenient moments. We propose a mobile framework, smartNoti, to carefully examine the user environment. The main contributions of our framework are: 1) developing an architecture to provide crucial information in a timely manner at a recognizable moment; 2) integrating, processing, training, and storing personalized latent features from heterogeneous data streams; 3) detecting user context transitions that might provide recognizable and available moments; and 4) predicting these moment and providing a notification message. The experimental validation on Intelligent Callback Reminder, which we implemented onan android application to notify a user missed or rejected call, demonstrates that our approach is effective. W e believe that our findings can lead to intelligent strategies to issue unobtrusive notifications on today’s smart phones at noextra cost, by using sensors and contextual factors.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
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