About This Project
Singapore faces recurring heat and haze risks while its population continues to age. We were inspired by a simple question: warnings tell us when conditions are bad, but where should help go first? This led us to propose HeatGuard, a tool that would combine live weather, elderly population and Active Ageing Centre data to identify areas where vulnerable residents may face greater heat risk and limited access to cooling support.
We plan to build HeatGuard using Databricks, cleaning and combining public datasets by planning area before calculating a risk score and displaying the results through an interactive dashboard. Our main challenge so far has been designing a risk score that is both useful and easy to understand. Through developing the concept, we've learned how different datasets can be combined to support more targeted, real-world decision-making.
Built With
- ai/bi
- databricks
- delta-lake
- genie
- lakeflow
- powerpoint
- python
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