A Survey on Conflict Detection in IoT-based Smart Homes
Bing Huang, Dipankar Chaki, Athman Bouguettaya, Kwok-Yan Lam

TL;DR
This survey reviews conflict detection methods in IoT-based smart homes, introducing a new taxonomy and model to classify conflicts, analyze recent approaches, and identify future research directions for improved system performance.
Contribution
It presents a novel conflict taxonomy and an advanced classification model, providing a comprehensive review of recent conflict detection techniques in IoT smart homes.
Findings
Classification of conflicts using the proposed model
Analysis of recent conflict detection approaches
Identification of open issues and future research directions
Abstract
As the adoption of IoT-based smart homes continues to grow, the importance of addressing potential conflicts becomes increasingly vital for ensuring seamless functionality and user satisfaction. In this survey, we introduce a novel conflict taxonomy, complete with formal definitions of each conflict type that may arise within the smart home environment. We design an advanced conflict model to effectively categorize these conflicts, setting the stage for our in-depth review of recent research in the field. By employing our proposed model, we systematically classify conflicts and present a comprehensive overview of cutting-edge conflict detection approaches. This extensive analysis allows us to highlight similarities, clarify significant differences, and uncover prevailing trends in conflict detection techniques. In conclusion, we shed light on open issues and suggest promising avenues…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsIoT and Edge/Fog Computing · Mobile Crowdsensing and Crowdsourcing · AI in Service Interactions
