An intelligent notification system using context from real-time personal activity monitoring

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 on an android application to notify a user missed or rejected call, demonstrates that our approach is effective. We believe that our findings can lead to intelligent strategies to issue unobtrusive notifications on today's smart phones at no extra cost, by using sensors and contextual factors.

Why are smartphones disruptive? An empirical study of smartphone use in real-life contexts

“…Another approach is to adapt notifications that users receive to the situation. While a classic study has investigated this idea by adding additional information about the call to the generic 'ring' of the phone (Milewski, 2006), recent applications have employed user preferences and machine learning to automatically detect and silence unwanted calls based on the devices' sensors and usage data (De Russis & Monge Roffarello, 2017;Fisher & Simmons, 2011;Oh, Jalali, & Jain, 2015;Schulze & Groh, 2014, 2016Smith, Lavygina, Ma, Russo, & Dulay, 2014;.…”

Optimizing Forecasted Activity Notifications with Reinforcement Learning

“…In daily activities, notifications can be utilized as reminders for specific events [ 38 , 39 ], location-based alerts [ 40 , 41 , 42 , 43 ], and activity prompts [ 6 , 42 , 43 , 44 ]. The importance of notifications has led to an increasing demand for user attention on smartphones, as notifications serve as the primary means of conveying information to the intended recipients.…”