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Identifying the time profile of everyday activities in the home using smart meter data

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conference contribution
posted on 29.10.2015, 11:11 by Charlie Wilson, Lina Stankovic, Vladmir Stankovic, Jing Liao, Michael Coleman, Richard Hauxwell-Baldwin, Tom Kane, Steven FirthSteven Firth, Tarek HassanTarek Hassan
Activities are a descriptive term for the common ways households spend their time. Examples include cooking, doing laundry, or socialising. Smart meter data can be used to generate time profiles of activities that are meaningful to households’ own lived experience. Activities are therefore a lens through which energy feedback to households can be made salient and understandable. This paper demonstrates a multi-step methodology for inferring hourly time profiles of ten household activities using smart meter data, supplemented by individual appliance plug monitors and environmental sensors. First, household interviews, video ethnography, and technology surveys are used to identify appliances and devices in the home, and their roles in specific activities. Second, ‘ontologies’ are developed to map out the relationships between activities and technologies in the home. One or more technologies may indicate the occurrence of certain activities. Third, data from smart meters, plug monitors and sensor data are collected. Smart meter data measuring aggregate electricity use are disaggregated and processed together with the plug monitor and sensor data to identify when and for how long different activities are occurring. Sensor data are particularly useful for activities that are not always associated with an energy-using device. Fourth, the ontologies are applied to the disaggregated data to make inferences on hourly time profiles of ten everyday activities. These include washing, doing laundry, watching TV (reliably inferred), and cleaning, socialising, working (inferred with uncertainties). Fifth, activity time diaries and structured interviews are used to validate both the ontologies and the inferred activity time profiles. Two case study homes are used to illustrate the methodology using data collected as part of a UK trial of smart home technologies. The methodology is demonstrated to produce reliable time profiles of a range of domestic activities that are meaningful to households. The methodology also emphasises the value of integrating coded interview and video ethnography data into both the development of the activity inference process.

History

School

  • Architecture, Building and Civil Engineering

Published in

European Council for an Energy Efficient Economy (ECEEE) 2015 Summer Study

Citation

WILSON, C. ...et al., 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) 2015 Summer Study, Toulon/Hyères, France, June 2015, pp. 933-946.

Publisher

REFIT

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

Notes

This is a conference paper.

ISBN

9789198048278;9789198048261

ISSN

2001-7960;1653-7025

Language

en

Location

Toulon/Hyères, France

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Keywords

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