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H. K. Palo
1 Introduction
A numerous range of new services and products including smart city, e-healthcare,
green energy, automobiles, retail, logistics, educational institutes, and environmental monitoring have been surfaced with the emergence of diverse and efficient IoT devices, sensors, connectivity, and communication networks [1]. The
support and collaboration industries, academia, and standardization bodies concerned
with telecommunication, informatics, and Semantic Web (SW) have set the desired
momentum in this field. There are three different aspects concerned with an IoT
paradigm that are intermixed and contribute to its definition [2]. These are, thingsoriented, Internet-oriented, and semantic-oriented. The things oriented IoT, refers
to elements such as the RFID tags with emphasizes on the related procedures that
enhance an object’s visibility like its tractability and status. The internet-oriented
IoT envisages promoting the Internet Protocol and its numerous versions (i.e., the
network technology to communicate different smart objects across the universe).
The semantic-oriented IoT provides and finds the requisite solutions for modeling,
describing, presenting, interconnecting, and processing things intelligently with
limited or no human intervention.
Among these three visions of IoT, the SW aims to combine Artificial intelligence
and knowledge engineering to represent, share, and integrate objects and related
information besides inferring new and up-date knowledge today. It helps to generate
machine-interpretable data which can be self-descriptive in the IoT domain. The
impact of Semantic IoT (SIoT) on this world is many and ever-growing. A recent
study shows an estimated 25 billion equipment and services will be connected to
the Internet by 2020 [3]. Such an astounding number of heterogeneous services
and devices will require automatic interconnections, interoperability and intelligent
communications to facilitate the end-users to track, locate, discover, represent, store,
and exchange huge amounts of information. This has led to the design and development of many technologies integrated into IoT such as the SW (i.e., ontologies,
semantic, annotation, etc.), Linked Data, and SW services [4–6]. The critical area of
concern is to integrate smart home appliances usually stuck between the early adoption phase and the mass-market phase owing to fragmentation [7]. The complexity
increases due to the involvement of numerous smart devices, operators, and IoT
service providers subject to time-consuming and complex operations, inadequate
research and innovations, vendor lock-in, glitches in overall performances, etc. To
be efficient, the IoT domain requires interoperability among these factors.
Semantics refers to the mutual understanding of the relevance of the meaning of
shared knowledge, information or data. The ever-increasing demand of heterogeneous sensors and smart devices to observe and measure surrounding variables to
gather valuable information makes incorporation of semantics in IoT. The obvious
effect of heterogeneity is a lack of interoperability among IoT devices and services.
This has made the SW system a widely accepted technology for modeling and integrating data collected from many sources. Nevertheless, such systems require a huge
amount of computing devices or resources due to the involvement of a large number
H. K. Palo
1 Introduction
A numerous range of new services and products including smart city, e-healthcare,
green energy, automobiles, retail, logistics, educational institutes, and environmental monitoring have been surfaced with the emergence of diverse and efficient IoT devices, sensors, connectivity, and communication networks [1]. The
support and collaboration industries, academia, and standardization bodies concerned
with telecommunication, informatics, and Semantic Web (SW) have set the desired
momentum in this field. There are three different aspects concerned with an IoT
paradigm that are intermixed and contribute to its definition [2]. These are, thingsoriented, Internet-oriented, and semantic-oriented. The things oriented IoT, refers
to elements such as the RFID tags with emphasizes on the related procedures that
enhance an object’s visibility like its tractability and status. The internet-oriented
IoT envisages promoting the Internet Protocol and its numerous versions (i.e., the
network technology to communicate different smart objects across the universe).
The semantic-oriented IoT provides and finds the requisite solutions for modeling,
describing, presenting, interconnecting, and processing things intelligently with
limited or no human intervention.
Among these three visions of IoT, the SW aims to combine Artificial intelligence
and knowledge engineering to represent, share, and integrate objects and related
information besides inferring new and up-date knowledge today. It helps to generate
machine-interpretable data which can be self-descriptive in the IoT domain. The
impact of Semantic IoT (SIoT) on this world is many and ever-growing. A recent
study shows an estimated 25 billion equipment and services will be connected to
the Internet by 2020 [3]. Such an astounding number of heterogeneous services
and devices will require automatic interconnections, interoperability and intelligent
communications to facilitate the end-users to track, locate, discover, represent, store,
and exchange huge amounts of information. This has led to the design and development of many technologies integrated into IoT such as the SW (i.e., ontologies,
semantic, annotation, etc.), Linked Data, and SW services [4–6]. The critical area of
concern is to integrate smart home appliances usually stuck between the early adoption phase and the mass-market phase owing to fragmentation [7]. The complexity
increases due to the involvement of numerous smart devices, operators, and IoT
service providers subject to time-consuming and complex operations, inadequate
research and innovations, vendor lock-in, glitches in overall performances, etc. To
be efficient, the IoT domain requires interoperability among these factors.
Semantics refers to the mutual understanding of the relevance of the meaning of
shared knowledge, information or data. The ever-increasing demand of heterogeneous sensors and smart devices to observe and measure surrounding variables to
gather valuable information makes incorporation of semantics in IoT. The obvious
effect of heterogeneity is a lack of interoperability among IoT devices and services.
This has made the SW system a widely accepted technology for modeling and integrating data collected from many sources. Nevertheless, such systems require a huge
amount of computing devices or resources due to the involvement of a large number