Inspiration
Natural disasters such as earthquakes, floods, and wildfires are becoming increasingly frequent and devastating. Inspired by the urgent need to protect lives and property, we designed AI-Saver, an intelligent agent aimed at predicting and preventing natural disasters through real-time data analysis.
What it does
AI-Saver is a machine learning-based agent that collects environmental data (temperature, humidity, seismic data, weather reports, etc.) from various sources. It processes this data to detect patterns and predict potential natural disasters before they happen. The system then sends early alerts to local authorities and affected populations, helping them prepare and potentially save lives.
How we built it
• Languages & Technologies: Python, Fetch.AI, TensorFlow, APIs for data collection (OpenWeather, Earthquake Data API).
• Machine Learning Models: Decision Trees, Neural Networks for pattern recognition and prediction.
• Platform: Devpost.
Challenges we faced
• Collecting relevant data from multiple sources in real-time.
• Ensuring predictions are accurate and reliable.
• Designing a simple and accessible user interface for non-technical users.
What’s next
We plan to integrate more data sources and improve the prediction algorithms for better accuracy. Collaboration with governments and non-profit organizations will also be explored to deploy AI-Saver globally.
Built With
- api
- data
- earthquake
- fetch.ai
- openweather-api
- python
- tensorflow
Log in or sign up for Devpost to join the conversation.