Ontology Driven Smart Health Service Integration.

Area of Science:

• Computer Science
• Health Informatics
• Artificial Intelligence

Background:

• The proliferation of Internet of Things (IoT) applications has significantly advanced technology in daily life.
• Smart healthcare services, an evolution of IoT, are crucial for stakeholders like patients and doctors, impacting socio-economic factors.
• Current research in the Internet of Health Things (IoHT) is fragmented, addressing specific diseases and services independently.

Purpose of the Study:

• To propose an ontology-based framework for integrating disparate smart healthcare services.
• To create a unified platform that facilitates shared knowledge and resources within smart healthcare.
• To address the disjointed nature of current IoHT research and development.

Main Methods:

• Development of an ontological framework to define and integrate healthcare services.
• Integration of services based on semantic relations, including similarities, differences, and dependencies.
• Derivation of data and process requirements for service integration from various smart healthcare applications.

Main Results:

• Evaluation of the proposed model using a two-step ontological testing method.
• Validation of model consistency through reasoning tools.
• Verification of retrieved data entities and their relations using querying tools for specific use-cases.

Conclusions:

• A novel approach for smart health service integration using ontological modeling and merging techniques has been established.
• The research provides a foundation for a more cohesive and efficient smart healthcare ecosystem.
• Future work will focus on enhancing model efficiency and optimizing query performance.