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Smart Components for Enabling Intelligent Web of Things Applications




Published: 2016 November

Buchtitel: International Conference on Intelligent Systems and Applications (INTELLI)
Verlag: IARIA
Nicht-referierte Veröffentlichung
BibTeX

Kurzfassung
We are currently witnessing an increased use of sensor technologies, abundant availability of mobile devices, and growing popularity of wearables, which enable the direct integration of their data as part of rich client applications in a multitude of different domains. In this context, the Internet of Things (IoT) promises the capability of connecting billions of devices, resources, and things together in an integrated way. However, what we are currently witnessing is the proliferation of isolated islands of custom IoT solutions. A first step towards enabling some interoperability in the IoT is to connect things to the Web and to use the Web stack, thereby conceiving the so-called Web of Things (WoT). However, even when a homogeneous access is reached through Web protocols, a common understanding is still missing, specifically in terms of heterogeneous devices, different programmable interfaces and diverse data formats and structures. Our work focuses on two main aspects: overcoming device and interface heterogeneity as well as enabling adaptable and scalable (i.e., intelligent) decentralised WoT applications. To this end, we present an approach for realising decentralised WoT solutions based on three main building blocks: 1) smart components as an abstraction of a unified approach towards realising the devices’ interfaces, communication mechanisms, semantics of the devices’ resources and capabilities, and decision logic; 2) adaptability of devices’ interfaces and interaction at runtime; 3) adaptability of the devices’ data structures and semantics at runtime. We show how our approach can be applied by introducing a reference smart component design, provide a thorough evaluation in terms of a proof-of-concept implementation of an example use case.


Projekt

ARVIDA



Forschungsgruppe

Web Science und Wissensmanagement


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