Abstract

Purpose – The key purpose of this paper is to overview the many issues related to the integration of social sensing and pervasive sensing in the support of adaptive context-aware services. Design/methodology/approach – From the analysis of existing proposals and prototypes, the authors found out that the process of integrating social and pervasive sensing can follow a limited number of approaches, which enables the authors to properly frame the proposals existing in the literature (and/or available as prototype infrastructures) according to a simple taxonomy, which is very useful to make the survey much more effective than a simple list of systems and proposals. Findings – The taxonomy shows that, when integrating social sensing with pervasive sensing, it is possible, at one extreme, to exploit social network as a mere source of information and have such information flow towards the infrastructure supporting the execution of pervasive computing services. At the other extreme, it is possible exploiting a social network as an infrastructure for the integration, by having data from pervasive devices flow towards social networks. In between the extremes, different means can consider to have social networks and pervasive infrastructures converge towards each other to enable the integration of social and pervasive sensing. Originality/value – Besides introducing the main concepts related to social sensing and framing the key approaches that can be undertaken to pursue the integration with traditional pervasive sensing, the authors go further discussing open issues and key research challenges behind their seamless integration.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.