Smart Diary: A Smartphone-Based Framework for Sensing, Inferring, and Logging Users' Daily Life

In this paper, we present Smart Diary, a novel smartphone based framework that analyzes mobile sensing data to infer, predict, and summarize people's daily activities, such as their behavioral patterns and life styles. Such activities are then used as the basis for knowledge representation, which generates personal digital diaries in an automatic manner. As users do not need to intentionally participate into this process, Smart Diary is able to make inferences and predictions based on a wide range of information sources, such as the phones' sensor readings, locations, and interaction history with the users, by integrating such information into a sustainable mining model. This model is specifically developed to handle heterogeneous and noisy sensing data, and is made to be extensible in that users can define their own logic rules to express short-term, mid-term, and long-term event patterns and predictions. Our evaluation results are based on the Android platform, and they demonstrate that the Smart Diary framework can provide accurate and easy-to-read diaries for end users without their interventions.