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Supporting Smart Home Scenarios Using OWL and SWRL Rules.

Roberto Reda1, Antonella Carbonaro1, Victor de Boer2

  • 1Department of Computer Science and Engineering, University of Bologna, 40136 Bologna, Italy.

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Summary
This summary is machine-generated.

Semantic Web technologies enhance Internet of Things (IoT) home automation by overcoming device heterogeneity and programming complexity. This approach uses logical inferences for advanced scenario programming beyond simple trigger-action rules.

Keywords:
IoTSAREFSWRLcognitive systemshome automationontologysmart home

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Internet of Things

Background:

  • Home automation systems suffer from device heterogeneity and limited programming paradigms.
  • Current Internet of Things (IoT) domotic devices are under-exploited due to these limitations.

Purpose of the Study:

  • To demonstrate Semantic Web technologies as a solution for IoT home automation interoperability and programming complexity.
  • To overcome the limitations of traditional trigger-action programming in smart home scenarios.

Main Methods:

  • Developed a knowledge-based home automation system.
  • Utilized Semantic Web Rule Language (SWRL) for scenario programming.
  • Combined IoT sensor data with formalized knowledge for logical inferences.

Main Results:

  • Successfully demonstrated a knowledge-based system for complex home automation scenarios.
  • SWRL enabled advanced scenario programming, surpassing trigger-action limitations.
  • Validated the approach within the standardized SAREF context.

Conclusions:

  • Semantic Web technologies offer a viable solution to enhance IoT home automation.
  • The proposed method improves interoperability and reduces programming complexity.
  • The approach is feasible and applicable in standardized smart home environments.