Ubiquitous Internet of Medical Things (U-IoMT) is a novel technology for collecting data and processing communication to a digital entity that is connected to a virtual cyber-physical system world and the real physical world . Each actuator and sensor object interprets their environment and real-world technologies, such as real-time location and embedded sensors. U-IoMT concepts are based on universal things or objects connected to RFID, actuators, biosensor devices, and smartphones. IoMT refers to sensor devices that are connected via mobile-to-mobile communication. These devices are identified through a unique ID to define virtual representation within the Internet . The semantic sensor web ontology for ubiquitous health care technology has been proposed by using extraction, semantic modeling, and reasoning . The medicare health system integrates the IoMT ontology (IoMT-O) with the effectiveness of ontology building and evaluation, as shown in Fig. 1 of the IoMT-O architecture.
The advancement of ontologies is considered focal in these endeavors. Ontologies are metadata that provide a controlled vocabulary of terms, and each term has a specific definition and machine-processable semantics. By defining shared and basic area speculations, ontologies enable two individuals and machines to provide adequate information. As a result, it plays a key role in empowering context-based access, interoperability, and correspondence over the Internet.
In the real world, the next-generation social impact employs numerous mobile technologies of smart health care. IoMT smart/portable devices can connect to Wi-Fi/IPv6, and they can monitor patient health status in real-time daily. The institutionalization strategy for displaying information involves initial sensor information based on philosophical standards that utilize the Protégé and Ontology web language (OWL) . As Protégé OWL has been included with an SWRL (semantic web rule language) manager, it allows for the modification of SWRL and OWL standard ontologies . Moreover, a context-awareness framework is proposed with the specific end goal of providing clients with customized human services administration.
The semantic sensor network (SSN) web of medical things technologies are the new Ubiquitous IoMT application known as the Semantic Web of Medical Things (SWoMT). The SSN ontology enables the representation of semantic sensing and actuating devices that are related to information pertaining to energy, security, and quality. The IoMT-O framework that describes the real-world entity (objects, sensors, and things) of spatial and temporal objects could detect data and events . In medical informatics, inquiries are made about the significant difficulties of the semantic web, the arrangement of controlled therapeutic administrations inside the clinical data frameworks, and semantic web interoperability. In the literature, only a few researchers have proposed utilizing a few ontologies based on semantic web to name restorative data for customized health care [7–9].
The W3C's implementation of OWL is critical to the semantic web and Internet metaphysics . OWL is a web-characterization dialect that is more expressive than other cosmology dialects such as RDFS . Semantic annotations are the process of combining semantic information and ontology domain concepts, as well as URLs. To transfer semantic IoMT service, the semantic annotation for IoMT entities and devices is used to annotate the semantic labels. As a result of the IoT increasing number of devices, IoT wireless technology will rapidly expand to approximately 60 billion IoT devices by 2021.
RDF encapsulates recognizing objects that use web identifiers and portray assets based on basic properties. This method could result in the creation of yet another meta-information producing system that utilizes semantic connections. It is an ontology with well-designed knowledge information, context sharing, reusability, and reasoning. Context-aware health ontology employs OWL-descriptive logic (OWL-DL) to define the common health domain, share information, and provide context information to software agents .
A sensor network in ubiquitous health IoMT environments for assisted patients resides within the IoT paradigm. To provide context-awareness in IoMT sensor networks, smart wearable health devices and an environmental system with a high-level knowledge ontology framework based in low-level sensor networks should be included. IoMT was initially intended to care for and monitor patients regularly via Wi-Fi connections and ultimately improve the quality of service. IoMTs primary goal is to activate various devices and connect them to a network. Another concept of IoT is everyday objects that are reliable, recognizable, locatable, addressable, and controllable via Wi-Fi through RFID, wireless LAN, or WAN. Some devices are intended for data storage, processing, and energy efficiency. The context ontology editing tool Protégé 5.4 was embedded in a health domain to evaluate the U-IoMT . Protégé is one of the best open-source ontologies with built-in reasoner and rules, such as FACT++, Pellet, Hermit, and RACER-based on Fuzzy logic. Choosing a good reasoner is essential in developing an effective ontology framework.
Section 2 introduces the related works. Section 3 describes the data modeling layer architecture for E-health care. Section 4 describes the ontological structure of data and the modeling. The major challenges of the communication layer, which involved millions of sensor devices connected to the network, were improved based on bandwidth and radio magnetic wave spectrum. Section 5 develops the ontology with the capability of monitor, simulating, and analyzing the health status and various chronic diseases in real-time. Finally, Sect. 6 provides the test analysis and conclusion.