The Indoor Air Quality Domain Ontology for the Development of COPD Self-Management System

Abstract

Indoor Air Quality is the main concern for many individuals, specifically since the Covid19 outbreaks. Internet of Things (IoT) devices or sensors detect and monitor indoor air pollutants. Indoor air pollution has a direct effect on human health in terms of respiratory conditions, cardiovascular problems, and endocrine disorders. There is a recognized need for providing a self-management system for patients affected by respiratory infections and indoor air pollutants. There has been substantial research undertaken on the role of indoor air quality monitoring systems. Previous research has indicated a potential association between indoor air quality and human respiratory health conditions such as Chronic Obstructive Pulmonary Disease (COPD). COPD is estimated to be the worlds third leading cause of death. However, the effect of indoor air quality on COPD patients has yet to be understood. The principal finding of this research is the development of an indoor air quality ontology domain model based on the ontology engineering methodology that is Human-Centered Ontology Engineering Methodology (HCOME), which will be helpful in the development of a COPD self-management system.

Keywords

• indoor air quality
• copd
• hcome
• ontology domain modeling
• knowledgebase systems
• e-health