Semantic IoT: The Key to Realizing IoT Value
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of sensors to build a smart environment. Thus, developing a cost-effective, semantically annotation IoT system with a limited number of resources and sensors has
an area of concern [8]. To tackle the issue, the authors have followed a lightweight
semantic annotation approach. The objective is to develop a resource-constrained
IoT platform with fewer sensors, lower response time and data size.
The SW provides a future vision or scope to quickly search and interpret data
or information by machines to accomplish numerous complex tasks concerned with
discovering, retrieving, blending, and executing the available Web information. It
depicts a set of data or information so connected that it is possible to process these
easily by machine rather than human operators. It can be presumed to be an extension
of the state-of-art World Wide Web (WWW) and can represent the data effectively
by linking the entire database available globally [9, 10]. As compared to the SW, the
SIoT operates in a more dynamic environment wherein there is a frequent change
in the meaning of data or annotations over time and space. It allows semantic functionalities such as object recommendations or search and facilitates massive IoT
data management. It plays a major role in the model, describe, integrate, interconnect, and process IoT intelligently or to scale-up or down the IoT infrastructure with
limited or no human intervention [11]. A semantic-based discovery service QoDisco
to address the device location, capabilities, context data type, quality, and contextual
situations has been proposed by the authors to develop an effective SIoT system.
It involves repositories storing resource descriptions based on an ontology-oriented
information model with multi-attribute and range querying abilities [12]. The use of
different approaches such as publish-subscribe interactions and the parallel interactions with multiple repositories has reduced the cost of semantic search as claimed
by the authors.
To summarize the SIoT provides the essential framework for interoperability,
consistency, discovery, scalability, composability, and reusability. It improves
human–machine interaction, analyses, processes and activities concerning IoT
resources, data, services, and automatic operations. It is more complex than SW,
demands continuous pre-processing, monitoring, filtering, annotation, aggregation,
and integration.
The SIoT aims to simulate the evolution of the existing Web by enabling the interaction of the available unstructured documents or information or data with the desired
accessibility. Its objective is to provide a well-defined meaning, adequately allowing
the people to work in coordination and co-operation, and enabling computers to be
more efficient [4]. The SW is driven and built based on the World Wide Web Consortium (W3C)’s Resource Description Framework (RDF). It is coined with Uniform
Resource Identifiers (URIs) syntaxes known as RDF syntaxes to represent data. The
inclusion of data to RDF files facilitates discover, search, assess, add or collect, and
process the web data by Web spiders or computer programs or web users with less
effort. Such an effort assists humans in multi-tasking operations such as information
retrieval, online bookings, online accessibility to dictionaries, etc.
The aims to achieve a few major objectives are summarized as
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of sensors to build a smart environment. Thus, developing a cost-effective, semantically annotation IoT system with a limited number of resources and sensors has
an area of concern [8]. To tackle the issue, the authors have followed a lightweight
semantic annotation approach. The objective is to develop a resource-constrained
IoT platform with fewer sensors, lower response time and data size.
The SW provides a future vision or scope to quickly search and interpret data
or information by machines to accomplish numerous complex tasks concerned with
discovering, retrieving, blending, and executing the available Web information. It
depicts a set of data or information so connected that it is possible to process these
easily by machine rather than human operators. It can be presumed to be an extension
of the state-of-art World Wide Web (WWW) and can represent the data effectively
by linking the entire database available globally [9, 10]. As compared to the SW, the
SIoT operates in a more dynamic environment wherein there is a frequent change
in the meaning of data or annotations over time and space. It allows semantic functionalities such as object recommendations or search and facilitates massive IoT
data management. It plays a major role in the model, describe, integrate, interconnect, and process IoT intelligently or to scale-up or down the IoT infrastructure with
limited or no human intervention [11]. A semantic-based discovery service QoDisco
to address the device location, capabilities, context data type, quality, and contextual
situations has been proposed by the authors to develop an effective SIoT system.
It involves repositories storing resource descriptions based on an ontology-oriented
information model with multi-attribute and range querying abilities [12]. The use of
different approaches such as publish-subscribe interactions and the parallel interactions with multiple repositories has reduced the cost of semantic search as claimed
by the authors.
To summarize the SIoT provides the essential framework for interoperability,
consistency, discovery, scalability, composability, and reusability. It improves
human–machine interaction, analyses, processes and activities concerning IoT
resources, data, services, and automatic operations. It is more complex than SW,
demands continuous pre-processing, monitoring, filtering, annotation, aggregation,
and integration.
The SIoT aims to simulate the evolution of the existing Web by enabling the interaction of the available unstructured documents or information or data with the desired
accessibility. Its objective is to provide a well-defined meaning, adequately allowing
the people to work in coordination and co-operation, and enabling computers to be
more efficient [4]. The SW is driven and built based on the World Wide Web Consortium (W3C)’s Resource Description Framework (RDF). It is coined with Uniform
Resource Identifiers (URIs) syntaxes known as RDF syntaxes to represent data. The
inclusion of data to RDF files facilitates discover, search, assess, add or collect, and
process the web data by Web spiders or computer programs or web users with less
effort. Such an effort assists humans in multi-tasking operations such as information
retrieval, online bookings, online accessibility to dictionaries, etc.
The aims to achieve a few major objectives are summarized as