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Agent-Based Simulation of Smart Beds With Internet-of-Things for Exploring Big Data Analytics
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Date : 2018-03-30
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Agent-Based Simulation of Smart Beds With Internet-of-Things for Exploring Big Data Analytic

Internet-of-Things (IoT) can allow healthcare professionals to remotely monitor patients by
analyzing the sensors outputs with big data analytics. Sleeping conditions are one of the most inuential
factors on health. However, the literature lacks of the appropriate simulation tools to widely support the
research on the recognition of sleeping postures. This paper proposes an agent-based simulation framework
to simulate sleeper movements on a simulated smart bed with load sensors. This framework allows one to
dene sleeping posture recognition algorithms and compare their outcomes with the poses adopted by the
sleeper. This novel presented ABS-BedIoT simulator allows users to graphically explore the results with
starplots, evolution charts, and nal visual representations of the states of the bed sensors. This simulator
can also generate logs text les with big data for applying ofine big data techniques on them. The source
code of ABS-BedIoT and some examples of logs are freely available from a public research repository. The
current approach is illustrated with an algorithm that properly recognized the simulated sleeping postures
with an average accuracy of 98%. This accuracy is higher than the one reported by an existing alternative
work in this area.
Attachments
Attachment 1:   ÷ 08078180.pdf(6.9MB)  
Attachment 2:   ÷ 15..pdf(2.7MB)