Abstract
The instrumental view of smart homes and their users is premised on active management of energy demand contributing to energy system objectives. In this chapter we explore a novel way of using data from smart home technologies (SHTs) to link energy consumption in homes to daily activities. We use activities as a descriptive term for the common ways households spend their time at home. These activities, such as cooking or laundering, are meaningful to households’ own lived experience. We set out a novel method for disaggregating a household’s electricity consumption down to the appliance level allowing us to make inferences about the activities occurring in the home in any given time period. We apply this method to analyse the pattern of activities over the course of one month in 10 of the homes participating in the SHT field trial described in Chap. 1. We show how both the energy intensity and temporal routines of different activities vary both within and between households. Our method also clearly reveals the complexities of everyday life at home which shapes the domestication of SHTs.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bertoldi P, Atanasiu B (2006) Residential lighting consumption and saving potential in the enlarged EU. In: Proceedings of 4th international conference on Energy Efficiency in Domestic Appliances and Lighting (EEDAL’06), 2006, pp 21–23
De Lauretis S, Ghersi F, Cayla J-M (2016) Time use, lifestyle and energy consumption: lessons from time use and budget data for French households. Paper presented at the energy: expectations and uncertainty, Bergen, Norway, 19–22 June 2016
DECC (2014) Smart metering implementation programme: smart metering equipment technical specifications version 1.58. Department of Energy and Climate Change (DECC), London, UK
Gram-Hanssen K (2014) New needs for better understanding of household’s energy consumption—behaviour, lifestyle or practices? Architectural Eng Des Manage 10(1–2):91–107
Katzeff C, Wangel J (2015) Social practices, households, and design in the smart grid. In: ICT innovations for sustainability. Springer, pp 351–365
Liao J, Elafoudi G, Stankovic L, Stankovic V (2014a) Non-intrusive appliance load monitoring using low-resolution smart meter data. In: IEEE international conference on Smart grid communications (SmartGridComm), IEEE, 2014, pp 535–540
Liao J, Stankovic L, Stankovic V (2014b) Detecting household activity patterns from smart meter data. In: International conference on Intelligent Environments (IE), IEEE, 2014, pp 71–78
Murray D, Liao J, Stankovic L, Stankovic V, Hauxwell-Baldwin R, Wilson C, Coleman M, Kane T, Firth S (2015) A data management platform for personalised real-time energy feedback. Paper presented at the 8th international conference on Energy Efficiency in Domestic Appliances and Lighting (EEDAL’15), Luzern, Switzerland, 26–18 August 2015
ONS (2000a) National survey of time use. Office of National Statistics (ONS), London, UK
ONS (2000b) Survey on time use: activity coding list. Office of National Statistics (ONS) & Eurostat, London, UK
Schwartz T, Stevens G, Jakobi T, Denef S, Ramirez L, Wulf V, Randall D (2014) What people do with consumption feedback: a long-term living lab study of a home energy management system. Interact Comput 27(6):551–576
Stankovic L, Wilson C, Liao J, Stankovic V, Hauxwell-Baldwin R, Murray D, Coleman M (2015) Understanding domestic appliance use through their linkages to common activities. In: 8th international conference on energy efficiency in domestic appliances and lighting, 2015
Wilson C, Stankovic L, Stankovic V, Liao J, Coleman M, Hauxwell-Baldwin R, Kane T, Hassan T, Firth S (2015) Identifying the time profile of everyday activities in the home using smart meter data. Paper presented at the European Council for an Energy Efficient Economy (ECEEE) summer study, Hyeres, France, 1–6 June 2015
Zeifman M, Roth K (2011) Nonintrusive appliance load monitoring: review and outlook. IEEE Trans on Consum Electron 57(1)
Zoha A, Gluhak A, Imran MA, Rajasegarar S (2012) Non-intrusive load monitoring approaches for disaggregated energy sensing: a survey. Sensors 12(12):16838–16866
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2017 The Author(s)
About this chapter
Cite this chapter
Stankovic, L., Stankovic, V., Liao, J., Wilson, C. (2017). Routines and Energy Intensity of Activities in the Smart Home. In: Smart Homes and Their Users . Human–Computer Interaction Series(). Springer, Cham. https://doi.org/10.1007/978-3-319-68018-7_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-68018-7_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-68017-0
Online ISBN: 978-3-319-68018-7
eBook Packages: Computer ScienceComputer Science (R0)