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Fuzzy Intelligence in Monitoring Older Adults with Wearables

Authors
  • Mrozek, Dariusz1
  • Milik, Mateusz1
  • Małysiak-Mrozek, Bożena2
  • Tokarz, Krzysztof2
  • Duszenko, Adam1
  • Kozielski, Stanisław1
  • 1 Silesian University of Technology,
  • 2 Computer Vision and Digital Systems, Silesian University of Technology,
Type
Published Article
Journal
Computational Science – ICCS 2020
Publication Date
May 25, 2020
Volume
12141
Pages
288–301
Identifiers
DOI: 10.1007/978-3-030-50426-7_22
PMCID: PMC7302848
Source
PubMed Central
Keywords
License
Unknown

Abstract

Monitoring older adults with wearable sensors and IoT devices requires collecting data from various sources and proliferates the number of data that should be collected in the monitoring center. Due to the large storage space and scalability, Clouds became an attractive place where the data can be stored, processed, and analyzed in order to perform the monitoring on large scale and possibly detect dangerous situations. The use of fuzzy sets in the monitoring and detection processes allows incorporating expert knowledge and medical standards while describing the meaning of various sensor readings. Calculations related to fuzzy processing and data analysis can be performed on the Edge devices which frees the Cloud platform from performing costly operations, especially for many connected IoT devices and monitored people. In this paper, we show a solution that relies on fuzzy rules while classifying health states of monitored adults and we investigate the computational cost of rules evaluation in the Cloud and on the Edge devices.

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