Development of a non-intrusive, data-driven algorithm for occupant detection using indoor air quality data

Forschungsstelle

INNOSUISSE

Projektnummer

51925.1 IP-EE

Projekttitel

Development of a non-intrusive, data-driven algorithm for occupant detection using indoor air quality data

Projekttitel Englisch

Development of a non-intrusive, data-driven algorithm for occupant detection using indoor air quality data

Texte zu diesem Projekt

	Deutsch	Französisch	Italienisch	Englisch
Kurzbeschreibung		-	-
Abstract		-	-	-

Kategorie	Text
Kurzbeschreibung (Deutsch)	Development of a non-intrusive, data-driven algorithm for occupant detection using indoor air quality data
Kurzbeschreibung (Englisch)	Development of a non-intrusive, data-driven algorithm for occupant detection using indoor air quality data
Abstract (Deutsch)	A robust, grey-box approach for occupant detection based on indoor air quality data is developed, using Oxygen At Work's previous development and Empa NEST's extensive measurement infrastructure and expertise in data-driven smart home solutions.