Deakin University
Browse
loke-representingand-2016.pdf (978.76 kB)

Representing and reasoning with the internet of things: a modular rule-based model for ensembles of context-aware smart things

Download (978.76 kB)
journal contribution
posted on 2016-03-09, 00:00 authored by Seng LokeSeng Loke
Context-aware smart things are capable of computational behaviour based on sensing the physical world, inferring context from the sensed data, and acting on the sensed context. A collection of such things can form what we call a thing-ensemble, when they have the ability to communicate with one another (over a short range network such as Bluetooth, or the Internet, i.e. the Internet of Things (IoT) concept), sense each other, and when each of them might play certain roles with respect to each other. Each smart thing in a thing-ensemble might have its own context-aware behaviours which when integrated with other smart things yield behaviours that are not straightforward to reason with. We present Sigma, a language of operators, inspired from modular logic programming, for specifying and reasoning with combined behaviours among smart things in a thing-ensemble. We show numerous examples of the use of Sigma for describing a range of behaviours over a diverse range of thing-ensembles, from sensor networks to smart digital frames, demonstrating the versatility of our approach. We contend that our operator approach abstracts away low-level communication and protocol details, and allows systems of context-aware things to be designed and built in a compositional and incremental manner.

History

Journal

EAI endorsed transactions on context-aware systems and applications

Volume

3

Issue

8

Article number

e1

Pagination

1 - 17

Publisher

EAI

Location

[Ghent, Belgium]

eISSN

2409-0026

Language

eng

Publication classification

C Journal article; C1.1 Refereed article in a scholarly journal

Copyright notice

2016, S.W. Loke

Usage metrics

    Research Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC