title: myBlackBox: Blackbox Mobile Cloud Systems for Personalized Unusual Event Detection.
abstract: We demonstrate the feasibility of constructing a novel and practical real-world mobile cloud system, called myBlackBox, that efficiently fuses multimodal smartphone sensor data to identify and log unusual personal events in mobile users' daily lives. The system incorporates a hybrid architectural design that combines unsupervised classification of audio, accelerometer and location data with supervised joint fusion classification to achieve high accuracy, customization, convenience and scalability. We show the feasibility of myBlackBox by implementing and evaluating this end-to-end system that combines Android smartphones with cloud servers, deployed for 15 users over a one-month period.
authors.affiliation: National Security Research Institute, Yuseong, Daejeon 305-600, Korea. junho.ahn@colorado.edu.
authors.forename: Junho
authors.initials: J
authors.lastname: Ahn
authors.affiliation: Department of Computer Science, University of Colorado, Boulder, CO 80309, USA. richard.han@colorado.edu.
authors.forename: Richard
authors.initials: R
authors.lastname: Han
keywords: behavior pattern; blackbox; fusion; mobile user; unusual event