Health Level 7

Rodrigues, Joel José P.C.; Compte, Sandra Sendra; Diez, Isabel de la Torra

doi:10.1016/b978-1-78548-091-1.50002-6

Cited by 2 publications

(2 citation statements)

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“…Exploiting, enriching and combining this data to develop smarter interoperable applications is becoming a great challenge. The semantic technology utilization does well in resolving the issue of interoperability among IoT devices [6]. Several semantic models [7] are introduced for describing the physical objects using Description Logics and ontologies to enable semantic interoperability.…”

Section: Hypothesis and Resultsmentioning

confidence: 99%

Secure Semantic Smart HealthCare (S3HC)

Tiwari

Jain

Abraham

et al. 2019

JWE

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Healthcare is a significant domain having a huge knowledge base, a significant part which comes from medical, diagnostic and imaging devices and sensors. The health status of patients may be monitored and managed remotely by performing reasoning over this knowledge base. Specialists in HealthCare facilities are required to handle large quantity of data generated and make decisions. However, the heterogeneous and complex nature and the huge amount of data generated; the way it is represented and presented; and the security challenges may overburden the core abilities of thinking and reasoning of even highly skilled and knowledgeable experts putting the lives of patients at risk. The situation may become even worse when data is coming from various healthcare devices and sensors which are themselves characterized by a number of representation and serialization formats. To address the various challenges in healthcare, this paper tries to represent and hence exchange the data collected by healthcare devices meaningfully and securely. This allows all healthcare devices to operate in conjunction with each other facilitating deeper insights and enabling generation of intelligent recommendations.To transfer the collected data from devices to the knowledge base and vice versa, a healthcare IoT ontology with sensors and actuators is developed. SPARQL queries and SWRL rules are composed to provide personalized services and alleviating the doctors' workload.

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Section: Hypothesis and Resultsmentioning

confidence: 99%

Secure Semantic Smart HealthCare (S3HC)

Tiwari

Jain

Abraham

et al. 2019

JWE

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show abstract

“…For example, the WHO operates projects for supporting strategies for e-Health applications [ 16 ]. HL7 and DICOM provide information exchange standards for e-Health systems to integrate easily into communications between devices [ 17 , 18 , 19 ]. Through the protocols and Application Program Interfaces (APIs) for heterogeneous frameworks, the e-Health devices are able to interact with each other to exchange data.…”

Section: Related Workmentioning

confidence: 99%

Design and Implementation of e-Health System Based on Semantic Sensor Network Using IETF YANG

Jin

Kim

2018

Sensors

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Recently, healthcare services can be delivered effectively to patients anytime and anywhere using e-Health systems. e-Health systems are developed through Information and Communication Technologies (ICT) that involve sensors, mobiles, and web-based applications for the delivery of healthcare services and information. Remote healthcare is an important purpose of the e-Health system. Usually, the eHealth system includes heterogeneous sensors from diverse manufacturers producing data in different formats. Device interoperability and data normalization is a challenging task that needs research attention. Several solutions are proposed in the literature based on manual interpretation through explicit programming. However, programmatically implementing the interpretation of the data sender and data receiver in the e-Health system for the data transmission is counterproductive as modification will be required for each new device added into the system. In this paper, an e-Health system with the Semantic Sensor Network (SSN) is proposed to address the device interoperability issue. In the proposed system, we have used IETF YANG for modeling the semantic e-Health data to represent the information of e-Health sensors. This modeling scheme helps in provisioning semantic interoperability between devices and expressing the sensing data in a user-friendly manner. For this purpose, we have developed an ontology for e-Health data that supports different styles of data formats. The ontology is defined in YANG for provisioning semantic interpretation of sensing data in the system by constructing meta-models of e-Health sensors. The proposed approach assists in the auto-configuration of eHealth sensors and querying the sensor network with semantic interoperability support for the e-Health system.

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Health Level 7

Cited by 2 publications

References 0 publications

Secure Semantic Smart HealthCare (S3HC)

Secure Semantic Smart HealthCare (S3HC)

Design and Implementation of e-Health System Based on Semantic Sensor Network Using IETF YANG

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