Ontology Engineering of an IoT System for Monitoring Hypertension

Internet of Things (IoT), Ubiquitous Computing, and Cloud Computing technologies can be used to build telemedicine systems to support the Pervasive Healthcare's holistic vision of providing healthcare anywhere, anytime, to anyone. According to the World Health Organization (WHO), Non-communicable diseases (NCDs) are one of the greatest health challenges since they cause about 70% of deaths worldwide. For some NCDs, such as hypertension, diabetes, asthma and obesity, ICT technologies allow continuous follow-up of patients, enabling them and their health professionals to exercise more active control of these diseases. In this context, we developed the Ontology-Driven IoT System for Monitoring Hypertension (ODIoT-SMH), which employs the aforementioned technologies for monitoring hypertensive patients and was designed following a three-layer architecture: the Sensor Layer contains the Sensor Platform built in a wearable IoT device, which captures the patient's vital signals blood pressure, heart rate and body temperature; the Fog Layer contains the Mobile App application that runs on the patient's mobile device, where the clinical data are aggregated and modelled to be presented to the patient; and the Cloud Layer contains the API Server and Web App applications, where the clinical data are processed, managed, and archived to be viewed and analysed by health professionals. To deal with semantic interoperability issues that arise when many different devices and system components must interoperate, this system encompasses an ontology-based semantic model that was designed, implemented and deployed at the Cloud Layer. This paper focuses on the development of the ODIoT-SMH ontology and shows its applicability and benefits.