sis 18: e4

Research Article

Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications

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  • @ARTICLE{10.4108/eai.13-7-2018.155866,
        author={Iqbal H. Sarker},
        title={Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications},
        journal={EAI Endorsed Transactions on Scalable Information Systems: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={SIS},
        year={2018},
        month={11},
        keywords={Mobile phone user, smartphone data, data science, behavioral analytics, mobile data mining, machine learning, data-driven decision making, contexts, context-awareness, ambient intelligence, intelligent mobile services, mobile systems and applications, pervasive computing, intelligent environment},
        doi={10.4108/eai.13-7-2018.155866}
    }
    
  • Iqbal H. Sarker
    Year: 2018
    Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications
    SIS
    EAI
    DOI: 10.4108/eai.13-7-2018.155866
Iqbal H. Sarker1,*
  • 1: Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne, VIC-3122, Australia
*Contact email: msarker@swin.edu.au

Abstract

Due to the popularity of smart mobile phones and context-aware technology, various contextual data relevant to users’ diverse activities with mobile phones is available around us. This enables the study on mobile phone data and context-awareness in computing, for the purpose of building data-driven intelligent mobile applications, not only on a single device but also in a distributed environment for the benefit of end users. Based on the availability of mobile phone data, and the usefulness of data-driven applications, in this paper, we discuss about mobile data science that involves in collecting the mobile phone data from various sources and building data-driven models using machine learning techniques, in order to make dynamic decisions intelligently in various day-to-day situations of the users. For this, we first discuss the fundamental concepts and the potentiality of mobile data science to build intelligent applications. We also highlight the key elements and explain various key modules involving in the process of mobile data science. This article is the first in the field to draw a big picture, and thinking about mobile data science, and it’s potentiality in developing various data-driven intelligent mobile applications. We believe this study will help both the researchers and application developers for building smart data-driven mobile applications, to assist the end mobile phone users in their daily activities.