Picture of person typing on laptop with programming code visible on the laptop screen

World class computing and information science research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.

Explore

A data management platform for personalised real-time energy feedback

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

[img]
Preview
Text (Murray-etal-EEDAL-2015-A-data-management-platform-for-personalised-real-time)
Murray_etal_EEDAL_2015_A_data_management_platform_for_personalised_real_time.pdf - Final Published Version

Download (328kB) | Preview

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.