CLIMATESAFE

Inspiration

My inspiration was basically due to impromptu natural disasters that happens not only in Nigeria but all over the whole and its ravaging effects on the economics situations of such countries

What it does

ClimateSafe is a mobile app that provides hyperlocal disaster alerts for floods, heatwaves, storms, and other climate risks. It combines AI forecasts, satellite data, and community reports to warn users in real time, show safe evacuation routes, identify nearby shelters, and support offline access for rural areas—helping communities stay prepared and safe.

How it works

ClimateSafe is built as a mobile-first platform with a cloud-connected backend. It integrates AI and machine learning models to analyze satellite imagery, weather data, and environmental sensors for disaster prediction. Users receive real-time alerts via push notifications or SMS, while community reports feed into a live dashboard for authorities. The app also supports offline access, maps evacuation routes, and displays shelters using GIS data.

Challenges we ran into

Data Availability & Accuracy: Collecting reliable, high-resolution satellite, weather, and environmental sensor data for hyperlocal predictions can be difficult, especially in remote regions.

AI Model Reliability: Designing machine learning models that accurately predict floods, heatwaves, and other climate events requires large historical datasets and careful tuning to avoid false alarms.

Connectivity & Offline Access: Many vulnerable communities have limited internet access, so ensuring alerts and maps work offline is critical.

Accomplishments that we're proud of

What we learned

What's next for CLIMATESAFE

Built With

• dart
• fastapi
• firebase
• gdal
• javascript
• kotlin
• python