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

Wilson, Charlie ORCID:, Lina, Stankovic, Stankovic, Vladimir, Liao, Jing, Coleman, Michael, Hauxwell-Baldwin, Richard, Kane, Tom, Firth, Steven and Hassan, Tarek (2015) Identifying the time profile of everyday activities in the home using smart meter data. In: Proceedings of the ECEEE Summer Study on Buildings. UNSPECIFIED, pp. 933-945.

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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.

Item Type: Book Section
Uncontrolled Keywords: sdg 7 - affordable and clean energy ,/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy
UEA Research Groups: University of East Anglia Schools > Faculty of Science > Tyndall Centre for Climate Change Research
Faculty of Science > Research Centres > Tyndall Centre for Climate Change Research
Depositing User: Pure Connector
Date Deposited: 25 Jul 2015 03:01
Last Modified: 26 Apr 2023 00:10


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