Zompopo: Mobile Calendar Prediction Based on Human Activities Recognition Using the Accelerometer and Cloud Services

Both cloud computing and mobile computing domains have advanced rapidly and are the promising technologies for the near future. Furthermore, the proliferation of mobile devices is fostering the emergence of ubiquitous environments, and thus the development of pervasive and context-aware applications is increasing. Mobile technologies are mainly drawing their attention to the clouds due to the increasing demand of the applications for processing power, storage space and energy. This paper introduces Zompopo, an Android application that provides an intelligent calendar, combining Google Calendar and the accelerometer sensor of the mobile, which allows the user to schedule his/her activities from the beginning of the day according previous week's activities. The application is explained with detailed architectural and technological choices. The application uses Map Reduce to analyze the accelerometer sensor data to deduce any diversions from the regular calendar activity, thus efficiently utilizing the cloud computing resources. A detailed performance analysis of the application is also provided, showing how mobile application benefit by going cloud-aware.