What it does

As young adults moving out of our parents' houses, it's important to truly understand how homeowners insurance works and what drives their premium or risk profile. We noticed that risk factors for homes are fragmented across multipe systems, yet they are rarely synthesized into a single, actionable view. We utilized the Gemini API to analyze multiple factors involved in a home’s risk assessment by combining raw soil‑moisture sensor data, homeowner survey inputs, and environmental conditions, then converting that information into a clear summary, risk assessment scores per category, and actionable steps users can take to reduce their overall risk and lower the likelihood of filing an insurance claim.

How we built it

  • Hardware: M5GO IoT Starter Kit + Moisture Sensor v1.4 running UIFlow 2.0 firmware
  • Backend: Node.js + Express server receiving device data and writing to Firestore
  • Database: Firebase Firestore for real‑time streaming and historical storage
  • Frontend: React + ApexCharts dashboard with hybrid live/manual visualization

Challenges we ran into

  • Backend routing and local network IP discovery while using a hotspot with the M5GO device

Accomplishments that we're proud of

  • Built a fully working IoT → backend → database → dashboard pipeline

What we learned

  • How to debug UIFlow 2.0 firmware and sensor drivers
  • How to structure a full‑stack IoT project with Firestore

What's next for Sleep Safe & Safe

We would like to include different sensors to collect different data and give more insights:

  • angle sensor
  • smart water shutoff sensor
  • CO2 Sensor
  • integrate Ting electricity sensor

Improve the satellite view feature:

  • Include risk markers to better pinpoint damaged areas
  • Further use that data to give better risk insights

Implement notifications:

  • Send notifications to phone number and email registered with account
  • Alerts will include:
  • severe weather advisory with checklist of suggested checks
  • any critical sensor data
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