New ontology FDD-ON standardizes HVAC fault detection

Researchers have developed FDD-ON, a novel ontology designed to standardize fault detection and diagnosis (FDD) for Variable Air Volume (VAV) HVAC systems. This ontology aims to overcome data interpretability and interoperability challenges by formally representing system components, fault types, symptoms, and impacts. FDD-ON provides a machine-interpretable foundation for querying diagnostic knowledge and developing applications like AI-driven maintenance decision-making systems, with evaluations showing its utility in advancing scalable and transparent FDD solutions. AI

IMPACT Standardizes data for AI-driven maintenance in HVAC systems.

RANK_REASON The item is a research paper detailing a new ontology for a specific technical domain. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.AI →

• alphaXiv
• Bibliographic Explorer
• CatalyzeX Code Finder for Papers
• Connected Papers
• CORE Recommender
• DagsHub
• FDD-ON
• Gotit.pub
• Hugging Face
• Influence Flower
• Litmaps
• ScienceCast
• scite Smart Citations
• VAV HVAC

• paper
• infra

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →