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Configuration of smart environments made simple combining visual modeling with semantic metadata and reasoning

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Abstract
We present an approach that combines semantic metadata and reasoning with a visual modeling tool to enable the goal-driven configuration of smart environments for end users. In contrast to process-driven systems where service mashups are statically defined, this approach makes use of embedded semantic API descriptions to dynamically create mashups that fulfill the user's goal. The main advantage of the presented system is its high degree of flexibility, as service mashups can adapt to dynamic environments and are fault-tolerant with respect to individual services becoming unavailable. To support end users in expressing their goals, we integrated a visual programming tool with our system. This tool enables users to model the desired state of their smart environment graphically and thus hides the technicalities of the underlying semantics and the reasoning. Possible applications of the presented system include the configuration of smart homes to increase individual well-being, and reconfigurations of smart environments, for instance in the industrial automation or healthcare domains.
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WEB-SERVICES

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Please use this url to cite or link to this publication:

Chicago
Mayer, Simon, Nadine Inhelder, Ruben Verborgh, Rik Van de Walle, and Friedemann Mattern. 2014. “Configuration of Smart Environments Made Simple Combining Visual Modeling with Semantic Metadata and Reasoning.” In 2014 INTERNATIONAL CONFERENCE ON THE INTERNET OF THINGS (IOT), 61–66. New york: Ieee.
APA
Mayer, S., Inhelder, N., Verborgh, R., Van de Walle, R., & Mattern, F. (2014). Configuration of smart environments made simple combining visual modeling with semantic metadata and reasoning. 2014 INTERNATIONAL CONFERENCE ON THE INTERNET OF THINGS (IOT) (pp. 61–66). Presented at the International Conference on the Internet of Things (IOT) , New york: Ieee.
Vancouver
1.
Mayer S, Inhelder N, Verborgh R, Van de Walle R, Mattern F. Configuration of smart environments made simple combining visual modeling with semantic metadata and reasoning. 2014 INTERNATIONAL CONFERENCE ON THE INTERNET OF THINGS (IOT). New york: Ieee; 2014. p. 61–6.
MLA
Mayer, Simon et al. “Configuration of Smart Environments Made Simple Combining Visual Modeling with Semantic Metadata and Reasoning.” 2014 INTERNATIONAL CONFERENCE ON THE INTERNET OF THINGS (IOT). New york: Ieee, 2014. 61–66. Print.
@inproceedings{8503551,
  abstract     = {We present an approach that combines semantic metadata and reasoning with a visual modeling tool to enable the goal-driven configuration of smart environments for end users. In contrast to process-driven systems where service mashups are statically defined, this approach makes use of embedded semantic API descriptions to dynamically create mashups that fulfill the user's goal. The main advantage of the presented system is its high degree of flexibility, as service mashups can adapt to dynamic environments and are fault-tolerant with respect to individual services becoming unavailable. To support end users in expressing their goals, we integrated a visual programming tool with our system. This tool enables users to model the desired state of their smart environment graphically and thus hides the technicalities of the underlying semantics and the reasoning. Possible applications of the presented system include the configuration of smart homes to increase individual well-being, and reconfigurations of smart environments, for instance in the industrial automation or healthcare domains.},
  author       = {Mayer, Simon and Inhelder, Nadine and Verborgh, Ruben and Van de Walle, Rik and Mattern, Friedemann},
  booktitle    = {2014 INTERNATIONAL CONFERENCE ON THE INTERNET OF THINGS (IOT)},
  isbn         = {978-1-4799-5154-3},
  keywords     = {WEB-SERVICES},
  language     = {eng},
  location     = {Cambridge, MA},
  pages        = {61--66},
  publisher    = {Ieee},
  title        = {Configuration of smart environments made simple combining visual modeling with semantic metadata and reasoning},
  year         = {2014},
}

Web of Science
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