BURP Proposal

From Geospatial Analytics and Applications
Revision as of 13:50, 28 February 2019 by Rebecca.goh.2016 (talk | contribs)
Jump to navigation Jump to search
BURP Logo.png

PROPOSAL

POSTER

PROJECT APPLICATION

RESEARCH PAPER


PROJECT DESCRIPTION

In recent years, the Ministry of Education (MOE) has been appointing new mergers between schools and relocating them. These schools include primary schools, secondary schools as well as junior colleges. The merging and relocation of schools would mean lesser schools in each neighbourhoods. This would affect the students' accessibility to certain schools, especially those in primary schools where parents need to send their children to schools. With more upcoming mergers of school by MOE, it is important for the government and schools to know the inconvenience in terms of time and distance travelled caused by the mergers and implement measures to ensure that these areas have better accessibility. Thus, our team aims to identify the HDB residential areas that are affected due to the merger of schools.


PROJECT OBJECTIVES
  1. Identify the accessibility of HDB residential areas to schools affected by the mergers.
  2. Analyze and highlight the affected HDB residential areas
  3. Identify clustering of these affected HDB residential areas
  4. Building an application to project our ideas and insights obtained based on our findings.


PROJECT MOTIVATION

With an increase in Singapore aging population, there are lesser residents that requires education services from nearby schools. Hence, government have been coming up with more school mergers. So our main reason to take up this project is to provide a proper visualisation of residential areas that are most affected by these mergers due to the lack of accessibility. Through our application, we hope let these affected areas gain attention from government to improve on their current accessibility.



PROJECT PROTOTYPE
Prototype v.1.png


PROJECT MILESTONES
BURP Milestone.png


TASKS ALLOCATION
Iteration Week Task In-charge
1 and 2 Week 2 to 7 Idea Development and Project Proposal All
3 Week 8 Wiki Update (Project Assessment) Rebecca
4 Week 9 Data Preparation Peng Chong
5 Week 10 to 11 Application Development and Deployment Brendo and Peng Chong
6 Week 12 Poster Submission Brendo and Rebecca
7 Week 13 Final Project Paper Submission All


KEY CHALLENGES
Key Challenges Description Solution
Cross Referencing of Data As there are many datasets involved, it is difficult to cross reference the data as they are of different level.
  1. Find more data online to merge connect the different data
  2. Consult prof for advise
  3. Find for packages helps to link data
Restriction of Public Api To calibrate data on routes, we used public api. However, the public api do not allow us to call more than 10,000 times.
  1. Host locally to call unlimited number of times.


DATA SOURCES
Data Set Format Attributes
HDB Property Information CSV
  • Block
  • Street
  • Residential Status
Postal Code Data CSV
  • Address
  • Block
  • Latitude & Longitude
  • Postal Code
  • X & Y coordinates
  • Road Name
General Information of Schools CSV
  • School Name
  • Address
  • Postal Code
Route Data CSV
  • Distance
  • Duration
  • Location
  • Destination