Developed an AI-powered system to assess flood damage by surveying 45,000 houses electronically. This system used machine learning algorithms to analyze survey data, predict damage levels, and streamline resource allocation for emergency response.
Key Features:
Automated Data Collection: Electronic surveys with real-time data transmission.
Damage Prediction: ML models to predict damage severity and resource needs.
Cost Savings: Reduced assessment costs and resource wastage by millions.
Technologies Used:
Frontend: AWS Amplify
Backend: Amazon Bedrock, AWS SageMaker, Kafka
Database: AWS RDS
Outcome:
Successfully deployed the system, resulting in significant cost savings and award recognition for innovation in government digital services.
