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A Generic Sensor Framework for Parallel and Continuous Data Processing / submitted by Alexander Eckmaier
AuthorEckmaier, Alexander
CensorNarzt, Wolfgang
PublishedLinz, 2018
Description91 Seiten : Illustrationen
Institutional NoteUniversität Linz, Masterarbeit, 2018
Document typeMaster Thesis
Keywords (GND)Datenverarbeitung / Gesundheit
URNurn:nbn:at:at-ubl:1-23162 Persistent Identifier (URN)
 The work is publicly available
A Generic Sensor Framework for Parallel and Continuous Data Processing [2.99 mb]
Abstract (English)

Being able to live self-reliantly and independently also with advancing age is one of the basic human desires, especially at an older age because in this case it is oftentimes a matter of pride. How to technically contribute to this aspect is the major motivational factor for this thesis which merely uses the SENEX project as its thought-provoking impulse. A well-thought-out design and implementation of a generic sensor framework for parallel and continuous data processing are what is needed to construct some sort of body surveillance system which monitors and records crucial vital signs and other sensor data in an unobtrusive way. This way, valuable conclusions can be drawn which, in the best case, lead to precious insight and intelligent inferences to better understand the human body. The focus of this framework lies upon its generic nature, simple configuration, and uncomplex extensibility. In this thesis, related work aspects, the framework itself including detailed architecture and implementation facets as well as process flow analyses, a personal study, and critical concluding comments are presented. It does neither encompass nor disclose any confidential SENEX characteristics or SENEX-related test results. However, it gives a deep understanding of the framework, the way it functions, and what can be achieved with it. In my case, I show the advantage of connecting several distinct sensors to determine a specific motion sequence over only having the data of one single sensor.

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