SilverSense

Inspiration

Singapore’s ageing population is growing rapidly, but social isolation risk is not evenly distributed across communities. Older adults who live alone, face financial vulnerability, or have limited access to community support may be at greater risk, yet the relevant information is spread across different public datasets.

This inspired me to design SilverSense as a way to bring these signals together and turn them into practical community care decisions. I also drew inspiration from risk based elderly support and social prescription approaches used in Taiwan, where social vulnerability is linked to different types of community intervention.

What I Learned

I learned that identifying a high risk area is only the first step. A useful decision support tool should also explain why an area is vulnerable and help community teams decide what action may be most appropriate.

This led me to structure SilverSense around four connected stages:

Identify → Explain → Act → Prioritise

I also learned that explainability is especially important in social care, since social workers and community planners need to understand the factors behind a risk score before acting on it.

How I Designed It

SilverSense combines Singapore open data on elderly population density, living arrangements, ComCare assistance, and Active Ageing Centre availability and capacity.

These signals are transformed into community level vulnerability features and combined into an explainable Social Isolation Vulnerability Score for each planning area.

The platform is designed to provide:

1. A Low, Medium, or High vulnerability classification
2. The main drivers contributing to each area’s risk
3. Recommended community responses based on the dominant risk pattern
4. A ranked list of priority areas for outreach and resource allocation

The longer term vision is to extend the platform with consented wearable and smartphone signals such as mobility, physical activity, routine, and sociability changes for earlier detection of emerging social vulnerability.

Challenges

The main challenge is that social isolation is complex and cannot be directly measured using public area level data alone. SilverSense therefore focuses on estimating community level vulnerability rather than identifying isolated individuals.

Another challenge is ensuring that the system remains interpretable and actionable. Instead of producing only a risk score, I designed the solution to connect each risk profile with a clear explanation and an appropriate community response.

My goal is to help move social care from reactive outreach toward earlier, more targeted, and more informed community support.

Built With

• analysis
• data.gov.sg
• databricks
• hdb
• machine-learning
• msf
• python
• singstat
• sql