Mockup: Facility Selection and Subzone Accessibility
Mockup: First- and Last-Mile Journey Analysis
Mockup: New Facility Accessibility Simulation

Inspiration

We chose C2 — MoveEasy because access to healthcare and community care depends on more than having public transport nearby. For elderly residents with mobility limitations, long walks to boarding stops or from alighting stops to a hospital, polyclinic or Active Ageing Centre can make a journey difficult.

We want to help urban planners identify these access gaps and assess where a proposed facility could improve accessibility for underserved areas.

How we plan to solve it

We propose an interactive map with two features:

Existing-facility assessment: Planners select a hospital, polyclinic or AAC to view colour-coded accessibility scores across Singapore’s subzones. They can then open a subzone and place a starting point within it to explore a public-transport journey that minimises combined first- and last-mile walking distance, with estimated total travel time shown alongside.
New-site simulation: Planners place a proposed facility on the map to compare subzone accessibility before and after, showing which areas benefit and by how much. The simulation will compare access against existing facilities of the same type.

Together, these features will help planners identify existing gaps and prioritise proposed facility locations for further assessment.

How we plan to build it

We will combine Census elderly population data, URA subzone boundaries, LTA pedestrian and public-transport datasets, and verified healthcare and community care facility locations.

Lakeflow Jobs will load the data into Delta tables. Databricks Python notebooks will clean records, standardise coordinates and construct the pedestrian and public-transport network, with Unity Catalog organising the tables and documenting their sources.

Python geospatial and routing libraries, together with SQL, will calculate accessibility scores and journey estimates. Databricks Apps will provide the interactive map and proposed-location simulation, while an AI/BI Dashboard will summarise accessibility gaps and before-and-after results.

This is our Round 1 proposal. Implementation and validation are planned for the two-week build sprint.