KSII Transactions on Internet and Information Systems (TIIS)

  • 제12권4호
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  • Pages.1396-1414
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  • 2018
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  • 1976-7277(pISSN)
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  • 1976-7277(eISSN)
한국인터넷정보학회 (Korean Society for Internet Information)
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IoT Healthcare Communication System for IEEE 11073 PHD and IHE PCD-01 Integration Using CoAP

  • Li, Wei (School of Electronics Engineering, Kyungpook National University) ;
  • Jung, Cheolwoo (School of Electronics Engineering, Kyungpook National University) ;
  • Park, Jongtae (School of Electronics Engineering, Kyungpook National University)
  • 투고 : 2017.08.07
  • 심사 : 2017.11.26
  • 발행 : 2018.04.30
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초록

With the proliferation of the Internet of Things (IoT) healthcare devices, significant interoperability issue arises where devices use proprietary data transfer protocols. The IHE PCD-01 standard has been suggested for the exchange of healthcare data in ISO/IEEE 11073 PHD data model. However, the PCD-01 is not efficient to be used in the IoT environment. This is because the use of SOAP for PCD-01 may be too complex to be implemented in the resource-constrained IoT healthcare devices. In this paper, we have designed a communication system to implement ISO/IEEE 11073 and IHE PCD-01 integration using the IETF CoAP. More specifically, we have designed the architecture and procedures, using CoAP, to seamlessly transmit the bio-signal from the tiny resource-constrained IoT healthcare devices to the server in a standardized way. We have also built the agent, gateway, and PCD-01 interface at the server, all of which are using the CoAP as a communication protocol. In order to evaluate the performance of the proposed system, we have used the PCD data to be transmitted over CoAP, MQTT, and HTTP. The evaluation of the system performance shows that the use of CoAP results in faster transaction and lesser cost than other protocols, with less battery power consumption.

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참고문헌

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피인용 문헌

  1. Security in IoMT Communications: A Survey vol.20, pp.17, 2018, https://doi.org/10.3390/s20174828
  2. Enhancements and Challenges in CoAP—A Survey vol.20, pp.21, 2018, https://doi.org/10.3390/s20216391
  3. Internet of Things-assisted intelligent monitoring model to analyze the physical health condition vol.29, pp.6, 2021, https://doi.org/10.3233/thc-213011