A data management platform for personalised real-time energy feedback

David Murray, Jing Liao, Lina Stankovic, Vladimir Stankovic, Richard Hauxwell-Baldwin, Charlie Wilson, Michael Coleman, Tom Kane, Steven Firth

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

This paper presents a data collection and energy fe edback platform for smart homes to enhance the value of information given by smart energy meter da ta by providing user-tailored real-time energy consumption feedback and advice that can be easily accessed and acted upon by the household. Our data management platform consists of an SQL server back-end which collects data, namely, aggregate power consumption as well as consumption of major appliances, temperature, humidity, light, and motion data. These data streams allow us to infer information about the household’s appliance usage and domestic activities, which in t urn enables meaningful and useful energy feedback. The platform developed has been rolled ou t in 20 UK households over a period of just over 21 months. As well as the data streams mentioned, q ualitative data such as appliance survey, tariff, house construction type and occupancy information a re also included. The paper presents a review of publically available smart home datasets and a desc ription of our own smart home set up and monitoring platform. We then provide examples of th e types of feedback that can be generated, looking at the suitability of electricity tariffs a nd appliance specific feedback.
LanguageEnglish
Title of host publicationProcededings of the 8th International Conference on Energy Efficiency in Domestic Appliances and Lighting
Subtitle of host publicationEEDAL’15
Number of pages15
Publication statusPublished - Aug 2015
Event8th International Conference on Energy Efficiency in Domestic Appliances and Lighting - Switzerland, Lucerne, United Kingdom
Duration: 26 Aug 201528 Aug 2015

Conference

Conference8th International Conference on Energy Efficiency in Domestic Appliances and Lighting
Abbreviated titleEEDAL'15
CountryUnited Kingdom
CityLucerne
Period26/08/1528/08/15

Fingerprint

Information management
Feedback
Domestic appliances
Atmospheric humidity
Electric power utilization
Servers
Energy utilization
Electricity
Monitoring
Temperature

Keywords

  • smart homes
  • real-time energy
  • smart energy meter
  • energy consumption

Cite this

Murray, D., Liao, J., Stankovic, L., Stankovic, V., Hauxwell-Baldwin, R., Wilson, C., ... Firth, S. (2015). A data management platform for personalised real-time energy feedback. In Procededings of the 8th International Conference on Energy Efficiency in Domestic Appliances and Lighting: EEDAL’15
Murray, David ; Liao, Jing ; Stankovic, Lina ; Stankovic, Vladimir ; Hauxwell-Baldwin, Richard ; Wilson, Charlie ; Coleman, Michael ; Kane, Tom ; Firth, Steven. / A data management platform for personalised real-time energy feedback. Procededings of the 8th International Conference on Energy Efficiency in Domestic Appliances and Lighting: EEDAL’15. 2015.
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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. in Procededings of the 8th International Conference on Energy Efficiency in Domestic Appliances and Lighting: EEDAL’15. 8th International Conference on Energy Efficiency in Domestic Appliances and Lighting, Lucerne, United Kingdom, 26/08/15.

A data management platform for personalised real-time energy feedback. / Murray, David; Liao, Jing; Stankovic, Lina; Stankovic, Vladimir; Hauxwell-Baldwin, Richard; Wilson, Charlie; Coleman, Michael; Kane, Tom; Firth, Steven.

Procededings of the 8th International Conference on Energy Efficiency in Domestic Appliances and Lighting: EEDAL’15. 2015.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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AU - Stankovic, Vladimir

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N2 - This paper presents a data collection and energy fe edback platform for smart homes to enhance the value of information given by smart energy meter da ta by providing user-tailored real-time energy consumption feedback and advice that can be easily accessed and acted upon by the household. Our data management platform consists of an SQL server back-end which collects data, namely, aggregate power consumption as well as consumption of major appliances, temperature, humidity, light, and motion data. These data streams allow us to infer information about the household’s appliance usage and domestic activities, which in t urn enables meaningful and useful energy feedback. The platform developed has been rolled ou t in 20 UK households over a period of just over 21 months. As well as the data streams mentioned, q ualitative data such as appliance survey, tariff, house construction type and occupancy information a re also included. The paper presents a review of publically available smart home datasets and a desc ription of our own smart home set up and monitoring platform. We then provide examples of th e types of feedback that can be generated, looking at the suitability of electricity tariffs a nd appliance specific feedback.

AB - This paper presents a data collection and energy fe edback platform for smart homes to enhance the value of information given by smart energy meter da ta by providing user-tailored real-time energy consumption feedback and advice that can be easily accessed and acted upon by the household. Our data management platform consists of an SQL server back-end which collects data, namely, aggregate power consumption as well as consumption of major appliances, temperature, humidity, light, and motion data. These data streams allow us to infer information about the household’s appliance usage and domestic activities, which in t urn enables meaningful and useful energy feedback. The platform developed has been rolled ou t in 20 UK households over a period of just over 21 months. As well as the data streams mentioned, q ualitative data such as appliance survey, tariff, house construction type and occupancy information a re also included. The paper presents a review of publically available smart home datasets and a desc ription of our own smart home set up and monitoring platform. We then provide examples of th e types of feedback that can be generated, looking at the suitability of electricity tariffs a nd appliance specific feedback.

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Murray D, Liao J, Stankovic L, Stankovic V, Hauxwell-Baldwin R, Wilson C et al. A data management platform for personalised real-time energy feedback. In Procededings of the 8th International Conference on Energy Efficiency in Domestic Appliances and Lighting: EEDAL’15. 2015