Conflict Detection in IoT-based Smart Homes
This addresses conflict management in IoT-based smart homes for residents, but it is incremental as it builds on existing knowledge graph and detection methods.
The authors tackled the problem of detecting conflicts between residents and IoT services in smart homes by proposing a framework that uses a knowledge graph and a conflict detection algorithm, achieving validation through experiments on real and synthesized datasets.
We propose a novel framework that detects conflicts in IoT-based smart homes. Conflicts may arise during interactions between the resident and IoT services in smart homes. We propose a generic knowledge graph to represent the relations between IoT services and environment entities. We also profile a generic knowledge graph to a specific smart home setting based on the context information. We propose a conflict taxonomy to capture different types of conflicts in a single resident smart home setting. A conflict detection algorithm is proposed to identify potential conflicts using the profiled knowledge graph. We conduct a set of experiments on real datasets and synthesized datasets to validate the effectiveness and efficiency of our proposed approach.