000 | 03319nam a22005055i 4500 | ||
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001 | 978-3-031-01526-7 | ||
003 | DE-He213 | ||
005 | 20240730164329.0 | ||
007 | cr nn 008mamaa | ||
008 | 220601s2018 sz | s |||| 0|eng d | ||
020 |
_a9783031015267 _9978-3-031-01526-7 |
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024 | 7 |
_a10.1007/978-3-031-01526-7 _2doi |
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_aUYS _2thema |
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_a621,382 _223 |
100 | 1 |
_aStanley, Michael. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _983954 |
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245 | 1 | 0 |
_aSensor Analysis for the Internet of Things _h[electronic resource] / _cby Michael Stanley, Jongmin Lee. |
250 | _a1st ed. 2018. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2018. |
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300 |
_aXXIII, 113 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aSynthesis Lectures on Algorithms and Software in Engineering, _x1938-1735 |
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505 | 0 | _aList of Figures -- List of Tables -- Preface -- Acknowledgments -- Nomenclature -- Introduction -- Sensors -- Sensor Fusion -- Machine Learning for Sensor Data -- IoT Sensor Applications -- Concluding Remarks and Summary -- Bibliography -- Authors' Biographies. | |
520 | _aWhile it may be attractive to view sensors as simple transducers which convert physical quantities into electrical signals, the truth of the matter is more complex. The engineer should have a proper understanding of the physics involved in the conversion process, including interactions with other measurable quantities. A deep understanding of these interactions can be leveraged to apply sensor fusion techniques to minimize noise and/or extract additional information from sensor signals. Advances in microcontroller and MEMS manufacturing, along with improved internet connectivity, have enabled cost-effective wearable and Internet of Things sensor applications. At the same time, machine learning techniques have gone mainstream, so that those same applications can now be more intelligent than ever before. This book explores these topics in the context of a small set of sensor types. We provide some basic understanding of sensor operation for accelerometers, magnetometers,gyroscopes, and pressure sensors. We show how information from these can be fused to provide estimates of orientation. Then we explore the topics of machine learning and sensor data analytics. | ||
650 | 0 |
_aSignal processing. _94052 |
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650 | 1 | 4 |
_aSignal, Speech and Image Processing. _931566 |
700 | 1 |
_aLee, Jongmin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _983956 |
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710 | 2 |
_aSpringerLink (Online service) _983959 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031000140 |
776 | 0 | 8 |
_iPrinted edition: _z9783031003981 |
776 | 0 | 8 |
_iPrinted edition: _z9783031026546 |
830 | 0 |
_aSynthesis Lectures on Algorithms and Software in Engineering, _x1938-1735 _983961 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-01526-7 |
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