• Developed a mobile app to predict floods in Selangor using an LSTM model.
• Utilized AWS Lambda for running prediction code efficiently.
• Stored prediction data in Amazon DynamoDB for quick access.
• Managed secure access to AWS services with IAM.
• Monitored app performance and logs with Amazon CloudWatch.
• Automated prediction schedules with AWS EventBridge.
• Used Amazon S3 for data storage and retrieval.
• Created interactive data visualizations in the Android app.
• Managed code versioning using GitHub.
• Automatically sent flood warning messages to users using AWS SNS and Firebase Cloud Messaging (FCM).

Awarded "Anugerah Panel Industri" at the UiTM Cawangan Kampus Melaka Kampus Jasin Final Year Project Exhibition for innovative application of predictive technology in flood management.

Please note that the API might experience issues as the Flask application is deployed on PythonAnywhere, which has a time limit and requires reactivation every 3 months.