Difference between revisions of "Elec3city"
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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 | | 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 | |
{| style="background-color:#ffffff ; margin: 3px 10px 3px 10px; width="80%"| | {| style="background-color:#ffffff ; margin: 3px 10px 3px 10px; width="80%"| | ||
| style="font-family:Open Sans, Arial, sans-serif; font-size:24px; border-top:solid #ffffff; border-bottom:solid #7A9FC4" width="1200px" | Project Description | | style="font-family:Open Sans, Arial, sans-serif; font-size:24px; border-top:solid #ffffff; border-bottom:solid #7A9FC4" width="1200px" | Project Description | ||
|} | |} | ||
| + | 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 16:59, 10 March 2019
Hi, we are making some updates to our project upon review and consultation, updating now - done by tonight, March 10!
|
Group Members |
Darren Choy
Fu Yu
Silvester Lim
| Project Title |
Visualizing possible causes of geospatial variation in Energy Consumption in Singapore with spatial interpolation techniques
| Project Description |
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.
