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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.
Sensors (Basel, Switzerland)
|June 10, 2022
Summary
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.
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.
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