A technique to enable the tracking of people for domestic energy monitoring applications
Hughes, TL 2015, A technique to enable the tracking of people for domestic energy monitoring applications , PhD thesis, University of Salford.
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Domestic energy consumption has increasingly become a cause for concern for governments, energy suppliers, and individual householders. Issues surrounding gas and electricity used in the home relate to the increasing cost of fuel, the rise in the incidence of fuel poverty, carbon dioxide emissions from fossil fuels contributing to climate change, security of supply due to geo-political disagreement and the age and condition of the existing energy infrastructure. While buildings and appliances have become more energy-efficient, usually driven by legislation, the energy-consuming behaviour of individuals is very difficult to change. Domestic energy monitoring has so far only been carried out at a household level, while the behaviour of individuals within households has remained ambiguous. There is a gap in current knowledge about how people use energy at home, mainly because it is very difficult to capture everyday behaviour without influencing the behaviour being observed. Initiatives and campaigns targeting domestic energy-consuming behaviour have been based on assumptions of how people use energy in their homes, and have been found to be ineffective. There is a need for an unobtrusive method of capturing domestic energy behaviour. This research presents a technique to deliver this requirement by enabling the tracking of people in their homes with a small number of cost-effective RFID (Radio Frequency ID) devices. Using this technique the location of multiple individuals wearing RFID tags can be determined, thereby creating an unobtrusive RTLS (Real Time Location System). This technique has been extensively evaluated through a series of tests within a typical 1940’s semi-detached house in North West England, and has been found to be able to successfully locate individuals to room level. If this RTLS data is matched with appliance level energy data, energy-consumption can be attributed to the individuals responsible, and personalised everyday energy-consuming behaviour can be established.
|Item Type:||Thesis (PhD)|
|Themes:||Built and Human Environment
|Schools:||Schools > School of Computing, Science and Engineering|
|Funders:||Garfield Weston Foundation|
|Depositing User:||TL Hughes|
|Date Deposited:||09 Nov 2015 14:23|
|Last Modified:||05 Apr 2016 19:32|
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