Considering Health and Family Dynamics: How is Home Temperature Decided?

The primary position of this research is to delineate design considerations for building a home energy management system that understands the dynamic nature of household structures; a system that can interact with situational variants and assist in temperature decision making, relieving user of added stressors during times of familial changes. This research discusses implications for building a home energy management system that considers household structures: changing needs when faced with a new heath situation or simply when life changes established routines. Home energy systems should be built to assist in decision making including how to set home temperature in order to maximize personal comfort and alleviate stress.

Content

Author and article information

Contributors

Germaine Irwin

Conference

Publication date: July 2016

Publication date (Print): July 2016

Pages: 1-3

Affiliations

[0001]University of Maryland Baltimore County

Department of Information Systems

1000 Hilltop Circle, ITE 430

Baltimore, MD 21250 USA

Article

DOI: 10.14236/ewic/HCI2016.66

SO-VID: 3fdc649b-4a51-4a6e-a37d-6952ae200225

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: Proceedings of the 30th International BCS Human Computer Interaction Conference

Conference acronym: HCI

Conference number: 30

Conference location: Bournemouth University, Poole, UK

Conference date: 11 - 15 July 2016

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Fusion

History

Product

1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/HCI2016.66

Self URI (journal page): https://ewic.bcs.org/

REFERENCES

E. CostanzaS.D. RamchurnN.R. Jennings 2012 Understanding domestic energy consumption through interactive visualisation: a field study New York, New York, USA ACM
S.M. Cristancho et al 2013 When surgeons face intraoperative challenges: a naturalistic model of surgical decision making The American Journal of Surgery 205 2 156 162
T. Dillahunt et al 2009 It’s not all about Green: energy use in low-income communities New York, New York, USA ACM
C. Fischer 2008 Feedback on household electricity consumption: a tool for saving energy? Energy efficiency 1 1 79 104
M. FréjusJ. Guibourdenche 2012 Analysing domestic activity to reduce household energy consumption Work 41 Supplement 1 539 548
J. Froehlich 2009 Promoting energy efficient behaviors in the home through feedback: The role of human-computer interaction Proc HCIC Workshop
C. GrevetJ. Mankoff 2009 Motivating sustainable behavior through social comparison on online social visualization HCI conference
G. Irwin et al 2015 Contextual insights into home energy relationships. 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops) 305 310
C. Jorge et al Watt-I-See: Probing Future Distributed Energy Scenarios nunonunes.info
L. Klein et al 2012 Coordinating occupant behavior for building energy and comfort management using multi-agent systems Automation in Construction 22 525 536
A.S. KulkarniK.C. WelchC.K. Harnett 2011 Modeling Human Behavior for Energy-Usage Prediction HCI International 2011 – Posters’ Extended Abstracts Communications in Computer and Information Science Berlin, Heidelberg Springer Berlin Heidelberg 298 302
Q. Li et al 2015 The Experiences of Chinese Couples Living With Cancer Cancer nursing 38 5 383 394
J. Lu et al 2010 The smart thermostat: using occupancy sensors to save energy in homes New York, New York, USA ACM
V.L. PatelD.R. KaufmanT.G. Kannampallil 2013 Diagnostic Reasoning and Decision Making in the Context of Health Information Technology Reviews of Human Factors and Ergonomics 8 1 149 190
J. PierceE. Paulos 2011 A phenomenology of human-electricity relations New York, New York, USA ACM
J. PierceE. Paulos 2012 Beyond energy monitors: interaction, energy, and emerging energy systems New York, New York, USA ACM
J. PierceD.J. SchianoE. Paulos 2010 Home, habits, and energy: examining domestic interactions and energy consumption New York, New York, USA ACM
G. RenR. HouriziE. O’Neill 2015 Situation awareness and home energy reduction: a study Proc SEEP2015
R. Sanson Fisher et al 2000 The unmet supportive care needs of patients with cancer. Cancer 88 1 226 237
D. Sloo et al 2014 User friendly interface for control unit
J. TanimotoA. HagishimaH. Sagara 2008 A methodology for peak energy requirement considering actual variation of occupants’ behavior schedules Building and Environment 43 4 610 619
R.A. Winett et al 1978 Effects of monetary rebates, feedback, and information on residential electricity conservation. Journal of Applied Psychology 63 1 73 80
R. YangM.W. Newman 2013 Learning from a learning thermostat: lessons for intelligent systems for the home New York, New York, USA ACM

Comments

Comment on this article

[1] E. CostanzaS.D. RamchurnN.R. Jennings 2012 Understanding domestic energy consumption through interactive visualisation: a field study New York, New York, USA ACM

[2] S.M. Cristancho et al 2013 When surgeons face intraoperative challenges: a naturalistic model of surgical decision making The American Journal of Surgery 205 2 156 162

[3] T. Dillahunt et al 2009 It’s not all about Green: energy use in low-income communities New York, New York, USA ACM

[4] C. Fischer 2008 Feedback on household electricity consumption: a tool for saving energy? Energy efficiency 1 1 79 104

[5] M. FréjusJ. Guibourdenche 2012 Analysing domestic activity to reduce household energy consumption Work 41 Supplement 1 539 548

[6] J. Froehlich 2009 Promoting energy efficient behaviors in the home through feedback: The role of human-computer interaction Proc HCIC Workshop

[7] C. GrevetJ. Mankoff 2009 Motivating sustainable behavior through social comparison on online social visualization HCI conference

[8] G. Irwin et al 2015 Contextual insights into home energy relationships. 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops) 305 310

[9] C. Jorge et al Watt-I-See: Probing Future Distributed Energy Scenarios nunonunes.info

[10] L. Klein et al 2012 Coordinating occupant behavior for building energy and comfort management using multi-agent systems Automation in Construction 22 525 536

[11] A.S. KulkarniK.C. WelchC.K. Harnett 2011 Modeling Human Behavior for Energy-Usage Prediction HCI International 2011 – Posters’ Extended Abstracts Communications in Computer and Information Science Berlin, Heidelberg Springer Berlin Heidelberg 298 302

[12] Q. Li et al 2015 The Experiences of Chinese Couples Living With Cancer Cancer nursing 38 5 383 394

[13] J. Lu et al 2010 The smart thermostat: using occupancy sensors to save energy in homes New York, New York, USA ACM

[14] V.L. PatelD.R. KaufmanT.G. Kannampallil 2013 Diagnostic Reasoning and Decision Making in the Context of Health Information Technology Reviews of Human Factors and Ergonomics 8 1 149 190

[15] J. PierceE. Paulos 2011 A phenomenology of human-electricity relations New York, New York, USA ACM

[16] J. PierceE. Paulos 2012 Beyond energy monitors: interaction, energy, and emerging energy systems New York, New York, USA ACM

[17] J. PierceD.J. SchianoE. Paulos 2010 Home, habits, and energy: examining domestic interactions and energy consumption New York, New York, USA ACM

[18] G. RenR. HouriziE. O’Neill 2015 Situation awareness and home energy reduction: a study Proc SEEP2015

[19] R. Sanson Fisher et al 2000 The unmet supportive care needs of patients with cancer. Cancer 88 1 226 237

[20] D. Sloo et al 2014 User friendly interface for control unit

[21] J. TanimotoA. HagishimaH. Sagara 2008 A methodology for peak energy requirement considering actual variation of occupants’ behavior schedules Building and Environment 43 4 610 619

[22] R.A. Winett et al 1978 Effects of monetary rebates, feedback, and information on residential electricity conservation. Journal of Applied Psychology 63 1 73 80

[23] R. YangM.W. Newman 2013 Learning from a learning thermostat: lessons for intelligent systems for the home New York, New York, USA ACM

Celebrating 65 years of The Computer Journal - free-to-read perspectives - bcs.org/tcj65