• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Architecture Support for Context-aware Adaptation of Rich Sensing Smartphone Applications

Vol. 12, No.1, January 31, 2018
10.3837/tiis.2018.01.012, Download Paper (Free):

Abstract

The performance of smartphone applications are usually constrained in user interactions due to resource limitation and it promises great opportunities to improve the performance by exploring the smartphone built-in and embedded sensing techniques. However, heterogeneity in techniques, semantic gap between sensor data and usable context, and complexity of contextual situations keep the techniques from seamless integration. Relevant studies mainly focus on feasibility demonstration of emerging sensing techniques, which rarely address both general architectures and comprehensive technical solutions. Based on a proposed functional model, this investigation provides a general architecture to deal with the dynamic context for context-aware automation and decision support. In order to take advantage of the built-in sensors to improve the performance of mobile applications, an ontology-based method is employed for context modelling, linguistic variables are used for heterogeneous context presentation, and semantic distance-based rule matching is employed to customise functions to the contextual situations. A case study on mobile application authentication is conducted with smartphone built-in hardware modules. The results demonstrate the feasibility of the proposed solutions and their effectiveness in improving operational efficiency.


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Cite this article

[IEEE Style]
Zhaozong Meng, "Architecture Support for Context-aware Adaptation of Rich Sensing Smartphone Applications," KSII Transactions on Internet and Information Systems, vol. 12, no. 1, pp. 248-268, 2018. DOI: 10.3837/tiis.2018.01.012

[ACM Style]
Meng, Z. 2018. Architecture Support for Context-aware Adaptation of Rich Sensing Smartphone Applications. KSII Transactions on Internet and Information Systems, 12, 1, (2018), 248-268. DOI: 10.3837/tiis.2018.01.012