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Final Thesis: Entwicklung Eines Intelligenten Raumplanungssystems Anhand Sensoren Für Luftqualität Unter Anwendung Verschiedener Machine Und Deep Learning Verfahren

Abstract: The thesis is targeting the question to predict a room’s occupation status without help of intrinsic sensors such as motion sensors or noise. Based on quantitative information about air composition, several machine learning algorithms are supposed to decide whether a meeting is terminated already, to release the specific resource for another booking. A second aspect aims at qualitative information. Studies showed that concentration decreases dramatically in bad air surroundings. Gathered subjective data and modern scientific approaches will be used to evaluate the indoor air quality and improve people’s satisfaction.

PDF: Master Thesis

Reference: Thilo Lars Kratzer. Entwicklung Eines Intelligenten Raumplanungssystems Anhand Sensoren Für Luftqualität Unter Anwendung Verschiedener Machine Und Deep Learning Verfahren. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2019.

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