Difference between revisions of "Elec3city"

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[[Elec3city|<font color="#3c3c3c"><strong>HOME</strong></font>]]
 
  
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[[Group06_Elec3city_Proposal|<font color="#3c3c3c"><strong>PROPOSAL</strong></font>]]
 
[[Group06_Elec3city_Proposal|<font color="#3c3c3c"><strong>PROPOSAL</strong></font>]]
  
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Group Members
 
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Darren Choy<br>
 
Fu Yu<br>
 
Silvester Lim<br>
 
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| style="font-family:Open Sans, Arial, sans-serif; font-size:24px; border-top:solid #ffffff; border-bottom:solid #7A9FC4" width="1200px" | Project Title
 
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Visualizing possible causes of geospatial variation in Energy Consumption in Singapore with spatial interpolation techniques
 
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| style="font-family:Open Sans, Arial, sans-serif; font-size:24px; border-top:solid #ffffff; border-bottom:solid #7A9FC4" width="1200px" | Project Description
 
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When it comes to the government’s push for efficient energy usage, most effort is expended on the efficiency of energy sources – e.g. using less carbon-intensive fuels (https://www.nea.gov.sg/our-services/climate-change-energy-efficiency/energy-efficiency/energy-efficient-singapore). However, hitherto, there has been scant statistical analysis on possible causes of inexpedient energy usage by households, with consideration of their varied age structure and the geospatial variation of environmental conditions (e.g. temperature’s effect on energy consumption).
 
 
Our team sees geospatial analytical tools (such as R) as thus far largely unexploited in exploring the origins of geospatial variation in energy consumption and is thus using spatial interpolation techniques (such as kriging) to provide an app which allows for authorities in Singapore such as the National Environment Agency to understand with data-driven evidence the origins of variation in Singapore household energy consumption so as to have more targeted efforts to reduce energy wastage.
 

Revision as of 17:44, 14 April 2019