Semantic Web Technologies
55
6.6 Semantic Web and IoT
IoT applications have the potential to contribute in many areas such as healthcare,
agriculture, automobile etc. which can facilitate to improve human life. It can be
predicated that IoT platforms are responsible for are transforming the landscape of
information and communication technology. This is clear from the growing usage of
internet-enabled gadgets in our everyday lives. These devices, via sensors, produce
large quantities of data that are analyzed by cloud platforms in order to develop IOT
applications. However, heterogeneity is the basic feature of the components of IOT
systems, which is also reflected in their generated data. Due to this heterogeneity of
data, interpretation, the proper exploitation and integration of IOT systems becomes
very difficult, leading to interoperability between different IOT systems. It is important to infer information from raw data collected to create interoperable, successful
IoT applications. Not only can the application of semantic techniques to IoT enable
interoperability, but it will also support effective data access, knowledge extraction
and integration [22].
OpenIot is a kind of first open source IoT project that enables IOT services in the
cloud platform to be semantically interoperable. Based on W3C Semantic Sensor
Networks (SSN), OpenIoT can collect data from any type of sensor (including mobile
sensors) with its proper semantic annotation. Using OpenIoT’s visual tools, users can
develop and deploy IoT applications with near zero programming [23].
FIESTA-IoT addresses seven-level semantic interoperability issues. It integrates
previously developed semantic-based projects such as OpenIoT, IoT-est, IoT-A, IoT6
etc. as well as non-semantic-based projects such as SmartSantander EU. Data level
ensures interoperability by annotating it semantically, Model level aligns existing IoT
ontologies. Query level queries unified bases of knowledge, reasoning level unifies
meaningful information. Service/Application level operates on “Experimentationas-a-Service (Eaas)” focused on “Linked Open Services” inspired by Linked Data.
Applicative domain level develops cross-domain/vertical applications [24].
In [25], Gergely Marcell Honti and Janos Abonyi took a brief analysis of the
Internet of Robotic Things (IoRT) related ontologies such as RoboEarth, Smart and
Networking Underwater Robots in Cooperation Meshes (SWARM) and Robotics and
Automation Core Ontology (CORA). They also focused on IoT applications such
as SCRIBED, Knowledge Model for city (Km4City),READY4SmartCities based on
semantic web technologies.
7 Conclusion
This chapter presents basic ideas, concepts and technologies used in Semantic Web
initiative. Semantic web is interpreted as web of data. Its main intension is to enable
structured and unstructured data source’s integration. To integrate them, these data
sources are represented in RDF format and their semantics is expressed using RDF
55
6.6 Semantic Web and IoT
IoT applications have the potential to contribute in many areas such as healthcare,
agriculture, automobile etc. which can facilitate to improve human life. It can be
predicated that IoT platforms are responsible for are transforming the landscape of
information and communication technology. This is clear from the growing usage of
internet-enabled gadgets in our everyday lives. These devices, via sensors, produce
large quantities of data that are analyzed by cloud platforms in order to develop IOT
applications. However, heterogeneity is the basic feature of the components of IOT
systems, which is also reflected in their generated data. Due to this heterogeneity of
data, interpretation, the proper exploitation and integration of IOT systems becomes
very difficult, leading to interoperability between different IOT systems. It is important to infer information from raw data collected to create interoperable, successful
IoT applications. Not only can the application of semantic techniques to IoT enable
interoperability, but it will also support effective data access, knowledge extraction
and integration [22].
OpenIot is a kind of first open source IoT project that enables IOT services in the
cloud platform to be semantically interoperable. Based on W3C Semantic Sensor
Networks (SSN), OpenIoT can collect data from any type of sensor (including mobile
sensors) with its proper semantic annotation. Using OpenIoT’s visual tools, users can
develop and deploy IoT applications with near zero programming [23].
FIESTA-IoT addresses seven-level semantic interoperability issues. It integrates
previously developed semantic-based projects such as OpenIoT, IoT-est, IoT-A, IoT6
etc. as well as non-semantic-based projects such as SmartSantander EU. Data level
ensures interoperability by annotating it semantically, Model level aligns existing IoT
ontologies. Query level queries unified bases of knowledge, reasoning level unifies
meaningful information. Service/Application level operates on “Experimentationas-a-Service (Eaas)” focused on “Linked Open Services” inspired by Linked Data.
Applicative domain level develops cross-domain/vertical applications [24].
In [25], Gergely Marcell Honti and Janos Abonyi took a brief analysis of the
Internet of Robotic Things (IoRT) related ontologies such as RoboEarth, Smart and
Networking Underwater Robots in Cooperation Meshes (SWARM) and Robotics and
Automation Core Ontology (CORA). They also focused on IoT applications such
as SCRIBED, Knowledge Model for city (Km4City),READY4SmartCities based on
semantic web technologies.
7 Conclusion
This chapter presents basic ideas, concepts and technologies used in Semantic Web
initiative. Semantic web is interpreted as web of data. Its main intension is to enable
structured and unstructured data source’s integration. To integrate them, these data
sources are represented in RDF format and their semantics is expressed using RDF