Ontology Development for Detecting Complex Events in Stream Processing: Use Case of Air Quality Monitoring

Yemson, Rose; Kabir, Sohag; Thakker, Dhavalkumar; Konur, Savas

Abstract

With the increasing amount of data collected by IoT devices, detecting complex events in real-time has become a challenging task. To overcome this challenge, we propose the utilisation of semantic web technologies to create ontologies that structure background knowledge about the complex event-processing (CEP) framework in a way that machines can easily comprehend. Our ontology focuses on Indoor Air Quality (IAQ) data, asthma patients’ activities and symptoms, and how IAQ can be related to asthma symptoms and daily activities. Our goal is to detect complex events within the stream of events and accurately determine pollution levels and symptoms of asthma attacks based on daily activities. We conducted a thorough testing of our enhanced CEP framework with a real dataset, and the results indicate that it outperforms traditional CEP across various evaluation metrics such as accuracy, precision, recall, and F1-score.

Citation

Yemson, R., Kabir, S., Thakker, D., & Konur, S. (2023). Ontology Development for Detecting Complex Events in Stream Processing: Use Case of Air Quality Monitoring. Computers, 12(11), Article 238. https://doi.org/10.3390/computers12110238

• Journal Article Type: Article
• Acceptance Date: Nov 13, 2023
• Online Publication Date: Nov 16, 2023
• Publication Date: Nov 1, 2023
• Deposit Date: Dec 10, 2024
• Publicly Available Date: Dec 10, 2024
• Journal: Computers
• Print ISSN: 2073-431X
• Electronic ISSN: 2073-431X
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 11
• Article Number: 238
• DOI: https://doi.org/10.3390/computers12110238
• Keywords: Complex events; Traditional complex event processing; Semantic web technology; Ontology; Internet of Things; Indoor air quality; Asthma
• Public URL: https://hull-repository.worktribe.com/output/4484827