Runtime Adaptability of Ambient Intelligence Systems Based on Component-Oriented Approach

M.C. Kaya, Alperen Eroğlu, Alper Karamanlioglu, Ertan Onur, B. Tekinerdogan, A.H. Dogru

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

Technological improvements of the Internet and connected devices cause increased user expectations. People want to be offered different services in nearly every aspect of their lives. It is a key point that these services can be reached seamlessly and should be dynamically available conforming to the active daily life of today’s people. This can be achieved by having intelligent environments along with smart appliances and applications. The concept of ambient intelligence arises from this need to react with users at runtime and keep providing real-time services under changing conditions. This chapter introduces a component-oriented ontology-based approach to develop runtime adaptable ambient intelligence systems. In this approach, the adaptability mechanism is enabled through a component-oriented method with variability-related capabilities. The outcome supports the find-and-integrate method from the idea formation to the executable system, and thus reducing the need for heavy processes for development. Intelligence is provided through ontology modeling that supports repeatability of the approach in different domains, especially when used in interaction with component variability. In this context, an example problem exploiting the variability in the density of a smart stadium network is used to illustrate the application of the component-driven approach.
Original languageEnglish
Title of host publicationGuide to ambient intelligence in the IoT environment
Subtitle of host publicationprinciples, technologies and applications
EditorsZaigham Mahmood
PublisherSpringer Verlag
Chapter4
Pages69-92
Number of pages25
ISBN (Electronic)9783030041731
ISBN (Print)9783030041724
DOIs
Publication statusPublished - Jan 2019

Publication series

NameComputer Communications and Networks
ISSN (Print)1617-7975
ISSN (Electronic)2197-8433

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