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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Languages: English
Types: Unknown
Subjects: built_and_human_env, energy
Residential energy use accounts for 29% of global energy consumption and 21% of global CO2 emissions, making the residential sector an important focal point in relation to the dual issues of climate change and resource depletion. Improving heating in households would also have important socio-economic impacts, especially in relation to the health of the occupants. For example, in 2008/09 there were an estimated 36,700 more deaths during the winter period in England and Wales compared to an average non-winter period. Much of this excess mortality has been attributed to “fuel poverty”, which is defined by the UK Government Department for Energy and Climate Change (DECC) as “households needing to spend more than 10% of income on fuel to maintain a satisfactory heating regime.”\ud Traditionally, Post Occupancy Evaluation (POE) is conducted against the prescribed performance specification and mainly relies on two activities; i) The effective collection of real world data and ii) the formulation of this data into models that allow trends and deviations to be observed. However, it is required to gain efficiencies by identifying potentially easier and more economical methods and tools for the collection of data such as wireless sensors.\ud Thus, the paper sets out a new vision of how future post occupancy evaluation in residential dwellings can be conducted. It explores the use of BIM (Building Information Modelling) that is progressively becoming more popular for developing building information throughout the building lifecycle. The paper employs a comparative study to build up greater understanding of the relationship between the fabric and the building use. Although the paper is grounded on the UK experience, it does also explore the international relevance of the issues.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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