Benutzer: Gast  Login
Titel:

Sensor Failure Detection in Ambient Assisted Living Using Association Rule Mining: Special Issue Sensors Technology for Smart Homes

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
ElHady, Nancy E.; Jonas, Stephan; Provost, Julien; Senner, Veit
Nicht-TUM Koautoren:
nein
Kooperation:
-
Abstract:
Ambient Assisted Living (AAL) is becoming crucial to help governments face the consequences of the emerging ageing population. It aims to motivate independent living of older adults at their place of residence by monitoring their activities in an unobtrusive way. However, challenges are still faced to develop a practical AAL system. One of those challenges is detecting failures in non-intrusive sensors in the presence of the non-deterministic human behaviour. This paper proposes sensor failure d...     »
Intellectual Contribution:
Discipline-based Research
Zeitschriftentitel:
Sensors (Basel, Switzerland)
Journal gelistet in FT50 Ranking:
nein
Jahr:
2020
Band / Volume:
20
Jahr / Monat:
2020-11
Heft / Issue:
23
Seitenangaben Beitrag:
21
Nachgewiesen in:
Scopus
Volltext / DOI:
doi:10.3390/s20236760
Verlag / Institution:
MDPI
Verlagsort:
Open Acces
Impact Factor:
3.275 (2019)
Eingereicht (bei Zeitschrift):
20.10.2020
Angenommen (von Zeitschrift):
22.11.2020
Publikationsdatum:
26.11.2020
Urteilsbesprechung:
0
Key publication:
Ja
Peer reviewed:
Ja
International:
Ja
commissioned:
not commissioned
Professional Journal:
Ja
Technology:
Ja
Interdisziplinarität:
Ja
Leitbild:
;
Ethics und Sustainability:
Nein
 BibTeX