Intelligent Home Heating Controller Using Fuzzy Rule Interpolation

Jie Li, Longzhi Yang, Hubert P. H. Shum, Graham Sexton, Yao Tan

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The reduction of domestic energy waste helps in achieving the legal binding target in the UK that CO2 emissions needs to be reduced by at least 34% below base year (1990) levels by 2020. Space heating consumes about 60% of the household energy consumption, and it has been reported by the Household Electricity Survey from GOV.UK, that 23% of residents leave the heating on while going out. To minimise the waste of heating unoccupied homes, a number of sensor-based and programmable controllers for central heating system have been developed, which can successfully switch off the home heating systems when a property is unoccupied. However, these systems cannot automatically preheat the homes before occupants return without manual inputs or leaving the heating on unnecessarily for longer time, which has limited the wide application of such devices. In order to address this limitation, this paper proposes a smart home heating controller, which enables a home heating system to efficiently preheat the home by successfully predicting the users’ home time. In particular, residents’ home time is calculated by employing fuzzy rule interpolation, supported by users’ historic and current location data from portable devices (commonly smart mobile phones). The proposed system has been applied to a real-world case with promising results shown.
Original languageEnglish
Publication statusPublished - 8 Sept 2015
EventUKCI 2015 - UK Workshop on Computational Intelligence - Exeter, UK
Duration: 8 Sept 2015 → …


ConferenceUKCI 2015 - UK Workshop on Computational Intelligence
Period8/09/15 → …


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