Dynamic Conflict Resolution of IoT Services in Smart Homes

TL;DR

This paper introduces a new conflict resolution framework for IoT services in smart homes, utilizing preference extraction and matrix factorization to effectively manage multi-resident conflicts.

Contribution

It presents a novel framework combining preference extraction and matrix factorization for conflict resolution in multi-resident smart home IoT environments.

Findings

The framework effectively resolves conflicts in real-world datasets.

Preference models improve IoT service management.

Experimental results demonstrate the approach's efficiency.

Abstract

We propose a novel conflict resolution framework for IoT services in multi-resident smart homes. The proposed framework employs a preference extraction model based on a temporal proximity strategy. We design a preference aggregation model using a matrix factorization-based approach (i.e., singular value decomposition). The concepts of current resident item matrix and ideal resident item matrix are introduced as key criteria to cater to the conflict resolution framework. Finally, a set of experiments on real-world datasets are conducted to show the effectiveness of the proposed approach.