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A Survey on Integrating Wireless Body Area Network Sensor Data with Semantic Web Technologies

EasyChair Preprint no. 3861

8 pagesDate: July 13, 2020

Abstract

Wireless body area network (WBAN) is a subset of the wireless sensor network (WSN). WBAN has a vital role in technology for remotely monitoring human physiological changes in healthcare. Many applications for wearable and plantable devices have used WBAN. Most wearable devices are designed with several sensors to monitor various aspects of the body. A problem of interoperability in WBAN sensor data arises from the many sensing devices from several manufacturers, which may be operating at different frequencies and generating data in various types of formats.  The heterogeneous nature of the WBAN sensor data limits the sharing and integration of other clinical data. There are several proposed approaches to address the challenges of the interoperability of the WBAN sensor. This paper presents a systematic review of some of the sensor data interoperability approaches using semantic web technology.  The knowledge in this paper is to provide a background for further investigations in the use of semantic web technologies for WBAN data integration.

Keyphrases: Linked Open Data, Semantic Interoperability, Semantic Web Technologies, sensor data, WBAN, Wireless Sensor Data

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:3861,
  author = {Joy Alatta and Joseph Cann},
  title = {A Survey on Integrating Wireless Body Area Network Sensor Data with Semantic Web Technologies},
  howpublished = {EasyChair Preprint no. 3861},

  year = {EasyChair, 2020}}
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