A Semantic Processing Framework for IoT-Enabled Communication Systems
Enterprise Collaboration Systems are designed in such a way to maximise the efficiency of communication and collaboration within the enterprise. With users becoming mobile, the Internet of Things can play a crucial role in this process, but is far from be
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INSIGHT Centre for Data Analytics, National University of Ireland, Galway, Ireland {ali.intizar,naomi.ono,mahedi.kaysar,alessandra.mileo}@insight-centre.org 2 Cisco Systems, Galway, Ireland [email protected]
Abstract. Enterprise Collaboration Systems are designed in such a way to maximise the efficiency of communication and collaboration within the enterprise. With users becoming mobile, the Internet of Things can play a crucial role in this process, but is far from being seamlessly integrated in modern online communications. In this paper, we showcase the use of a solution that goes beyond today’s ad-hoc integration and processing of heterogeneous data sources for static and streaming data, providing more flexible and efficient processing techniques that can bridge the gap between IoT and online Enterprise Communication Systems. We document the technologies used for sensor deployment, sensor data acquisition based on the OpenIoT framework, and stream federation. Our main contributions are the following, i) we present a conceptual architecture of IoT-enabled Communication Systems, that builds upon existing frameworks for semantic data acquisition, and tools to enable continuous processing, discovery and federation of dynamic data sources based on Linked Data; ii) we present a semantic information model for representing and linking IoT data, social data and personal data by re-using and extending the existing standard semantic models; iii) we evaluate the performance of virtualisation of IoT sources based on OpenIoT in our testbed and show the impact of transmission, annotation and data storage, as well as initial results on scalability of RDF stream query processing in such a framework, providing guidelines and directions for optimisation. Keywords: IoT · RDF stream processing · Stream federation munication systems · OpenIoT · Linked data
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Introduction
Enterprise communication systems currently and historically have been primarily aimed at person to person communication. Users of such systems typically This research is sponsored by Science Foundation Ireland (SFI) grant No. SFI/12/RC/2289 and Cisco Systems. c Springer International Publishing Switzerland 2015 M. Arenas et al. (Eds.): ISWC 2015, Part II, LNCS 9367, pp. 241–258, 2015. DOI: 10.1007/978-3-319-25010-6 14
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interact with an endpoint such as a phone, video system or unified communications software client capable of multi-modal communications. Communication modes typically consist of instant messaging, voice, video and voicemail to allow individuals or groups to communicate in real time. Such systems have not historically enabled open machine to machine or machine to person communication. The emergence of Internet of Things (IoT) provides the potential to enable communication between sensory devices and communication systems using open interfaces, but this potential is under investigated and few solutions have existed in isolation. As a result, the flexible integration of a large amount of multi-modal data streams from diverse
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