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Current Technologies
Published in Ravi Ramakrishnan, Loveleen Gaur, Internet of Things, 2019
Ravi Ramakrishnan, Loveleen Gaur
This refers to separating data and content files from the application code so that machines and people can reason and understand this in real time. For the IoT data to transition from being raw data to insights, data with semantic annotations, interoperable formats and adaptable and context-aware solutions are required. Although the IoT has defined frameworks, semantic technologies are needed for integration of IoT data. XML is one of the forefront semantic languages currently being used for M2M communication; however, it lacks a semantic model and has a surface model only and there are multiple domain specific tags that cannot be machine interpreted unless programmed. As the IoT devices tend to become more autonomous and plug and play, there is a need for extending the semantic web to a semantic sensor web to give information a well-defined meaning for autonomous interaction. Resource Description Framework (RDF), a W3C standard, consists of triplets or sentences with subject, property, and object, for example, “Sensor,” “hasType,” “temperature” or “Node,” “hasLocation,” “RoomX.” Every resource that can be an IoT device will have a universal identifier or URI. Semantic technologies can make the IoT more interoperable, enable data access, help in resource discovery by ways of broadcast, and help in processing of data.
Evolution of Embedded Internet
Published in K. R. Rao, Zoran S. Bojkovic, Bojan M. Bakmaz, Wireless Multimedia Communication Systems, 2017
K. R. Rao, Zoran S. Bojkovic, Bojan M. Bakmaz
Existing semantic sensor web technologies enable the integration of sensors into the Web. It was difficult to foresee the wealth of current web applications back when the Web was first created, yet now we have seen how widely adopted the Web has become. Likewise, it is difficult to predict how people will come to use the semantic Web of things. Using sensor data is clearly beneficial, because then integration with knowledge from arbitrary services is possible. For example, sensor data can be linked to geographic data, user-generated data, scientific data, and so on. A strong indicator of whether this line of development will be successful in the long run is also provided by the exponential growing amount of linked data.
Present and future of semantic web technologies: a research statement
Published in International Journal of Computers and Applications, 2021
The semantic sensor web is an expansion of the sensor web where sensor nodes swap and process data automatically without any human interference. The major components of the semantic sensor web are ontologies, query languages semantic annotation (comment), and rule languages. Ontologies serve as dictionaries that contain the definitions of all concepts used by sensor web. Semantic Sensor Network Ontology (SSNO) contains sensors, procedures, and their observations. Semantic annotation language, for example RDF and RDFa, is used for annotating the sensor’s measurement and observation. Reasoning service provides inferences on existing facts and rules that are defined via SWRL by which we extract additional information. All of the above-mentioned information forms the backbone of the semantic layer. SWTs play a very important role in the sensor network because through them, we infer semantic information from the raw data gathered by sensors. Hence, we can utilize meaningful information in many smart applications like health care, meteorology and environment observation, and so on.
Ontology-Based Modelling and Information Extracting of Physical Entities in Semantic Sensor Networks
Published in IETE Journal of Research, 2019
Mohammad Ahmadinia, Ali Movaghar, Amir Masoud Rahmani
The Semantic Sensor Web is a marriage of sensor and Semantic Web technologies. The semantic sensor web adds semantic web technologies including ontology to sensor web. Ontologies can help the better management of query and data aggregation of the sensor web. Ontology is a knowledgebase in which a computer-processable collection of knowledge is available about the world as collection of facts [1]. Every fact is a RDF triple, that includes two entities and a relation between them [2]. So far, several ontologies have been presented for the semantic presentation of sensor networks and the data received by them; for example, CSIRO [3], OntoSensor [4], Coastal environment sensor network (CESN) [5], Ontonym-Sensor [6] and SSN [7].