A Method for Mapping Sensor Data to SSN Ontology

Zhang, Xiaoming; Zhao, Yunping; Liu, Wanming

doi:10.14257/ijunesst.2015.8.9.31

Cited by 18 publications

(8 citation statements)

References 15 publications

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“…In agricultural areas, some researches have combined the sensor network with the semantic web on the basis of the SSN ontology. [12]…”

Section: What Is Ontology? [11]mentioning

confidence: 99%

Data Capturing and Retrieval From Wireless Sensor Networks Using Semantic Web

Pandey¹,

Panchal²

2019

IJCET

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The Internet of Things is giving a bright future and with establishment and maturity of wireless sensor networks, it can be truly realised for the various purposes of human endeavour. The paper deals with challenge to integrate the data coming from heterogeneous sensor networks coming from various geographical locations. A Sensor Web Registry is proposed to achieve this task. The outcome of this effort is further realised by using Semantic Web Technologies like Ontologies, OWL, SPARQL and Python. The paper used all this practically using a Micaz Sensor Boards with Zigbee protocol in a lab setup.

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“…In agricultural areas, some researches have combined the sensor network with the semantic web on the basis of the SSN ontology. [12]…”

Section: What Is Ontology? [11]mentioning

confidence: 99%

Data Capturing and Retrieval From Wireless Sensor Networks Using Semantic Web

Pandey¹,

Panchal²

2019

IJCET

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“…More and more studies are concentrating on applying data semantization in smart homes, healthcare and weather forecasting for monitoring inhabitants’ and environments’ abnormity and providing significant guidance and help. Zhang [ 12 ] proposes a system architecture used for transforming sensor data to semantic expression formats, which consists of three parts, semantic annotation, producing mapping file and transforming with semantics. Razzak [ 13 ] also depicts an architecture dealing with sensor data in which the responsible component for adding semantics is a publisher creating channels to equip data with semantic notifications.…”

Section: Overviewmentioning

confidence: 99%

A Survey of Data Semantization in Internet of Things

Shi

Zhu

2018

Sensors

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With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by multi-modal sensors or devices show great differences in formats, domains and types, which poses challenges for machines to process and understand. Therefore, adding semantics to Internet of Things becomes an overwhelming tendency. This paper provides a systematic review of data semantization in IoT, including its backgrounds, processing flows, prevalent techniques, applications, existing challenges and open issues. It surveys development status of adding semantics to IoT data, mainly referring to sensor data and points out current issues and challenges that are worth further study.

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“…In the work in [18], they proposed a method to map sensor data to SSN ontology, translating the sensor data in databases into the RDF which conforming to SSN ontology. They first extract the sensor data from data sources, and manually annotate the sensor data using a mapping schema.…”

Section: Related Workmentioning

confidence: 99%

“…The observable properties of the sensors include their survival range or accuracy of measurement under defined external conditions. Many sensors need to keep track of time and location to produce meaningful results and, hence, are combined with further sensors to sensor systems such as weather stations [18]. In the case of ITS, the sensors can be located into the vehicles and into different infrastructure elements, for example as part of bridges, roads, signs, etc.…”

Section: The Ssn Ontologymentioning

confidence: 99%

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

Fernández

Ito

2017

IEICE Trans. Inf. & Syst.

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SUMMARYIntelligent transportation systems (ITS) are a set of technological solutions used to improve the performance and safety of road transportation. Since one of the most important information sources on ITS are sensors, the integration and sharing the sensor data become a big challenging problem in the application of sensor networks to these systems. In order to make full use of the sensor data, is crucial to convert the sensor data into semantic data, which can be understood by computers. In this work, we propose to use the SSN ontology to manage the sensor information in an intelligent transportation architecture. The system was tested in a traffic light settings application, allowing to predict and avoid traffic accidents, and also for the routing optimization.

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A Method for Mapping Sensor Data to SSN Ontology

Abstract: Abstract

Cited by 18 publications

References 15 publications

Data Capturing and Retrieval From Wireless Sensor Networks Using Semantic Web

Data Capturing and Retrieval From Wireless Sensor Networks Using Semantic Web

A Survey of Data Semantization in Internet of Things

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

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