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English (United Kingdom)

Changing Mobile Data Analysis through Deep Learning

Year: 2017
Type of Publication: Article Keywords: mobile data analysis, deep learning, context-awareness, human activity recognition, accelerometer data
Journal: accepted for publication in the IEEE IT Professional Mobile Data Analytics
Situational and context awareness is becoming more and more important on the course towards intelligent machines and devices, offering a comprehensive toolset for improving our quality of life. The increased computational capacity of personal/smart devices, and their constantly increasing capabilities for sensing, allow for a large amount of collected data to be stored, processed and transmitted over mobile devices and networks. As a result, fast processing and analysis of this mobile data is becoming a big challenge. In this article, we start from the presentation of common mobile context-aware applications and a reference to the current practices and approaches on mobile data analysis, and propose the use of deep learning for analyzing sensor data from mobile devices, while we discuss open issues related to this approach.