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Erschienen in:
Improving Automatic Classifiers Through Interaction Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Detection of Behavioral Data Based on Recordings from Energy Usage Sensor

verfasst von : Piotr Augustyniak

Erschienen in: Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

Monitoring of human behavior in the natural living habitat requires a hidden yet accurate measurement. Several previous attempts showed, that this can be achieved by recording and analysing interactions of the supervised human with sensorized equipment of his or her household. We propose an imperceptible single-sensor measurement, already applied for energy usage profiling, to detect the usage of electrically powered domestic appliances and deduct important facts about the operator’s functional health. This paper proposes a general scheme of the system, discusses the personalization and adaptation issues and reveals benefits and limitations of the proposed approach. It also presents experimental results showing reliability of device detection based on their load signatures and areas of applicability of the load sensor to analyses of device usage and human performance.

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Vorheriges Kapitel Similarities, Dissimilarities and Types of Inner Products for Data Analysis in the Context of Machine Learning
Nächstes Kapitel Regularization Methods for the Analytical Statistical Reconstruction Problem in Medical Computed Tomography
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Metadaten
Titel
Detection of Behavioral Data Based on Recordings from Energy Usage Sensor
verfasst von
Piotr Augustyniak
Copyright-Jahr
2016
Buch
Artificial Intelligence and Soft Computing

Print ISBN: 978-3-319-39383-4

Electronic ISBN: 978-3-319-39384-1

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-39384-1_12

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