Group06 Elec3city Proposal
Contents
Project Motivation
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.
Project Objective
Deliver a dynamic (interactive) application that provides authorities such as the National Environment Agency and Housing Development Board with the ability to:
- View monthly and yearly temperature geospatial variation in Singapore, and compare that to energy consumption at building level granularity
- View housing composition (e.g. age, income and race) geospatial variation, and compare that to energy consumption at a building level granularity
so as to make data-informed, targeted decisions to promote reduction of energy usage among varying types of households in Singapore, where hitherto there has been a blanket approach.
Data
Literature Review
Methodology:
Learning Points:
Areas for improvement:
Approach
Techniques:
Web Application Design
Design Inspiration
The dashboard design is inspired by https://stanleyadion.shinyapps.io/AmazeingCrop
Initial Storyboard
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Project Challenges
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| 1. | Technical Challenge | The proposed geovisualization including bivariate choropleth maps and box-plots by planning zones and dwelling type is complex. The group may encounter technical challenges such as finding relevant R packages and functions when building the visualization. |
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Project Timeline
Gantt Chart of Team's Timeline - FULL Updated Version
Snapshot of Gantt Chart (as of 3 March 2019)
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