LivingCare - An autonomously learning, human centered home automation system: Collection and preliminary analysis of a large dataset of real living situations

Publikation: Beiträge in SammelwerkenAufsätze in SammelwerkenForschungbegutachtet

Standard

LivingCare - An autonomously learning, human centered home automation system : Collection and preliminary analysis of a large dataset of real living situations. / Eckert, Ralf; Müller, Sebastian; Glende, Sebastian; Gerka, Alexander; Hein, Andreas; Welge, Ralph.

Ambient Assisted Living: 9. AAL-Kongress, Frankfurt/M, Germany, April 20 - 21, 2016. Hrsg. / Reiner Wichert; Beate Mand. Cham : Springer International Publishing AG, 2017. S. 55-72 (Advanced Technologies and Societal Change).

Publikation: Beiträge in SammelwerkenAufsätze in SammelwerkenForschungbegutachtet

Harvard

Eckert, R, Müller, S, Glende, S, Gerka, A, Hein, A & Welge, R 2017, LivingCare - An autonomously learning, human centered home automation system: Collection and preliminary analysis of a large dataset of real living situations. in R Wichert & B Mand (Hrsg.), Ambient Assisted Living: 9. AAL-Kongress, Frankfurt/M, Germany, April 20 - 21, 2016. Advanced Technologies and Societal Change, Springer International Publishing AG, Cham, S. 55-72. https://doi.org/10.1007/978-3-319-52322-4_4

APA

Eckert, R., Müller, S., Glende, S., Gerka, A., Hein, A., & Welge, R. (2017). LivingCare - An autonomously learning, human centered home automation system: Collection and preliminary analysis of a large dataset of real living situations. in R. Wichert, & B. Mand (Hrsg.), Ambient Assisted Living: 9. AAL-Kongress, Frankfurt/M, Germany, April 20 - 21, 2016 (S. 55-72). (Advanced Technologies and Societal Change). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-52322-4_4

Vancouver

Eckert R, Müller S, Glende S, Gerka A, Hein A, Welge R. LivingCare - An autonomously learning, human centered home automation system: Collection and preliminary analysis of a large dataset of real living situations. in Wichert R, Mand B, Hrsg., Ambient Assisted Living: 9. AAL-Kongress, Frankfurt/M, Germany, April 20 - 21, 2016. Cham: Springer International Publishing AG. 2017. S. 55-72. (Advanced Technologies and Societal Change). https://doi.org/10.1007/978-3-319-52322-4_4

Bibtex

@inbook{d40eea165d46469cb2c87940d35f110c,
title = "LivingCare - An autonomously learning, human centered home automation system: Collection and preliminary analysis of a large dataset of real living situations",
abstract = "Within the scope of LivingCare, a BMBF funded research project, a real senior residence was equipped with a large amount of home automation sensors. More than sixty sensors and actuators were installed in this apartment. This automa-tion system is working totally passive in the background. It doesn't perform any actions. All actions performed by hu-mans like switching light on or off, setting the temperature and the usage of electric devices like TVs will only be recorded as data and not performed by the system. This data is collected over a period of 18 months. Thus, one of the largest mobility and characteristics datasets based on home automation sensors will be acquired. This data will be the foundation for developing autonomously learning algorithms. During the second project phase these algorithms will start to control functions of the home automation system. The projects objective is to develop an autonomously learning home automation system that automatically adapts to the resident's behavior. The system will be able to grow with the users needs. With all the possible data collected it will be able to support daily actions, recognize behavior changes over timer and will be able to call help in emergency situations.",
keywords = "Informatics, home automation, Internet of Things, IoT, reinforcement learning, autonomously learning, real life data, field trail, Gait speed, Test Person, Sensor Event, Movement Sensor, Occupation Time",
author = "Ralf Eckert and Sebastian M{\"u}ller and Sebastian Glende and Alexander Gerka and Andreas Hein and Ralph Welge",
year = "2017",
doi = "10.1007/978-3-319-52322-4_4",
language = "English",
isbn = "978-3-319-52321-7",
series = "Advanced Technologies and Societal Change",
publisher = "Springer International Publishing AG",
pages = "55--72",
editor = "Reiner Wichert and Beate Mand",
booktitle = "Ambient Assisted Living",
address = "Switzerland",

}

RIS

TY - CHAP

T1 - LivingCare - An autonomously learning, human centered home automation system

T2 - Collection and preliminary analysis of a large dataset of real living situations

AU - Eckert, Ralf

AU - Müller, Sebastian

AU - Glende, Sebastian

AU - Gerka, Alexander

AU - Hein, Andreas

AU - Welge, Ralph

PY - 2017

Y1 - 2017

N2 - Within the scope of LivingCare, a BMBF funded research project, a real senior residence was equipped with a large amount of home automation sensors. More than sixty sensors and actuators were installed in this apartment. This automa-tion system is working totally passive in the background. It doesn't perform any actions. All actions performed by hu-mans like switching light on or off, setting the temperature and the usage of electric devices like TVs will only be recorded as data and not performed by the system. This data is collected over a period of 18 months. Thus, one of the largest mobility and characteristics datasets based on home automation sensors will be acquired. This data will be the foundation for developing autonomously learning algorithms. During the second project phase these algorithms will start to control functions of the home automation system. The projects objective is to develop an autonomously learning home automation system that automatically adapts to the resident's behavior. The system will be able to grow with the users needs. With all the possible data collected it will be able to support daily actions, recognize behavior changes over timer and will be able to call help in emergency situations.

AB - Within the scope of LivingCare, a BMBF funded research project, a real senior residence was equipped with a large amount of home automation sensors. More than sixty sensors and actuators were installed in this apartment. This automa-tion system is working totally passive in the background. It doesn't perform any actions. All actions performed by hu-mans like switching light on or off, setting the temperature and the usage of electric devices like TVs will only be recorded as data and not performed by the system. This data is collected over a period of 18 months. Thus, one of the largest mobility and characteristics datasets based on home automation sensors will be acquired. This data will be the foundation for developing autonomously learning algorithms. During the second project phase these algorithms will start to control functions of the home automation system. The projects objective is to develop an autonomously learning home automation system that automatically adapts to the resident's behavior. The system will be able to grow with the users needs. With all the possible data collected it will be able to support daily actions, recognize behavior changes over timer and will be able to call help in emergency situations.

KW - Informatics

KW - home automation

KW - Internet of Things

KW - IoT

KW - reinforcement learning

KW - autonomously learning

KW - real life data

KW - field trail

KW - Gait speed

KW - Test Person

KW - Sensor Event

KW - Movement Sensor

KW - Occupation Time

U2 - 10.1007/978-3-319-52322-4_4

DO - 10.1007/978-3-319-52322-4_4

M3 - Contributions to collected editions/anthologies

SN - 978-3-319-52321-7

T3 - Advanced Technologies and Societal Change

SP - 55

EP - 72

BT - Ambient Assisted Living

A2 - Wichert, Reiner

A2 - Mand, Beate

PB - Springer International Publishing AG

CY - Cham

ER -

DOI