Semantic IoT Interoperability and Data Analytics Using …
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for effective and economical performance. In Syntactic Interoperability, common
data models and formats need to be followed whereas in Semantic Interoperability,
the information is interpreted and shared without ambiguity for information having
similar meanings.
3.1 IoT Interoperability Challenges
The major IoT interoperability challenge is to enable consistent resource allocation
and to ease the interoperability between different IoT platforms. The inconsistency
between IoT platforms results in platform dependency and applications unable to
run on multiple platforms. In such a scenario, there is a need for standardization in
certain areas to find a solution to the problems related to IoT interoperability [16].
The certain challenges of IoT interoperability are as follows:
(a) Variation in IoT Infrastructure.
(b) Variation in devices and their libraries.
(c) Different data formats.
(d) Applications developed are unable to work on cross-platform or on different
domains.
(e) There is no proper streamlining in IoT resource sharing.
(f) Inconsistency between different IoT platforms.
3.2 Web Ontology Framework for Semantic Interoperability
in IoT
The framework has been proposed for the semantic web in the medical sector shown
in Fig. 2. In the proposed framework, the patient query is monitored by the medical
specialist in the specialized area. The symptoms of patients are preprocessed which
involves the (a) patient past history, (b) medical prescriptions already diagnosed, (c)
Clinical Records, (d) lab tests, etc.
In order to know the symptoms of the patient, the doctor monitors the same
remotely using IoT devices. The interoperability in IoT needs to resolve the issues
related to devices, network, schema format, etc. The semantic interoperability enables
multiple platforms, applications to exchange information in a meaningful way on
the web-enabled platform. The knowledge base of the semantic web involves the
(a) Frame structures, (b) XML, (c) Predicate Logic, (d) UML modeling technique,
(d) Logic Rules, (e) RDF (Resource Description Framework), etc. for uniformity in
schema, syntax, and semantics.
The vocabulary related to patient symptoms is being checked in the knowledge
base for finding the prognosis having similar meaning or terminology and finally
after gathering the desired information, the web-based diagnostic results may be
generated. The ontologies can be expressed in different forms which are as follows:
249
for effective and economical performance. In Syntactic Interoperability, common
data models and formats need to be followed whereas in Semantic Interoperability,
the information is interpreted and shared without ambiguity for information having
similar meanings.
3.1 IoT Interoperability Challenges
The major IoT interoperability challenge is to enable consistent resource allocation
and to ease the interoperability between different IoT platforms. The inconsistency
between IoT platforms results in platform dependency and applications unable to
run on multiple platforms. In such a scenario, there is a need for standardization in
certain areas to find a solution to the problems related to IoT interoperability [16].
The certain challenges of IoT interoperability are as follows:
(a) Variation in IoT Infrastructure.
(b) Variation in devices and their libraries.
(c) Different data formats.
(d) Applications developed are unable to work on cross-platform or on different
domains.
(e) There is no proper streamlining in IoT resource sharing.
(f) Inconsistency between different IoT platforms.
3.2 Web Ontology Framework for Semantic Interoperability
in IoT
The framework has been proposed for the semantic web in the medical sector shown
in Fig. 2. In the proposed framework, the patient query is monitored by the medical
specialist in the specialized area. The symptoms of patients are preprocessed which
involves the (a) patient past history, (b) medical prescriptions already diagnosed, (c)
Clinical Records, (d) lab tests, etc.
In order to know the symptoms of the patient, the doctor monitors the same
remotely using IoT devices. The interoperability in IoT needs to resolve the issues
related to devices, network, schema format, etc. The semantic interoperability enables
multiple platforms, applications to exchange information in a meaningful way on
the web-enabled platform. The knowledge base of the semantic web involves the
(a) Frame structures, (b) XML, (c) Predicate Logic, (d) UML modeling technique,
(d) Logic Rules, (e) RDF (Resource Description Framework), etc. for uniformity in
schema, syntax, and semantics.
The vocabulary related to patient symptoms is being checked in the knowledge
base for finding the prognosis having similar meaning or terminology and finally
after gathering the desired information, the web-based diagnostic results may be
generated. The ontologies can be expressed in different forms which are as follows: