The Cloudburst Detection System is an innovative Android app designed to predict and mitigate the impact of cloudbursts using machine learning models and real-time weather data. This app aims to save lives and protect property by providing accurate and timely cloudburst predictions.
- Real-Time Data Integration: Integrates real-time weather data from the OpenMeteo API to provide users with up-to-the-minute information, critical for cloudburst prediction.
- Machine Learning Models: Utilizes advanced machine learning models trained on meteorological datasets to enhance the accuracy of cloudburst predictions.
- User-Centric Design: Features a user-friendly interface tailored for mobile devices, with functionalities such as push notifications and location-based alerts to enhance user engagement.
- Ease of Accessibility: Easily accessible with a single tap on a smartphone, making it convenient for users to check weather updates on the go.
- Accuracy: 91.756%
- Benefits:
- Strong at capturing non-linear patterns in meteorological data.
- Robust performance even with noisy data.
- Accuracy: 89.134%
- Benefits:
- Effective in handling class imbalance, crucial for rare cloudburst events.
- Provides valuable insights into the importance of meteorological parameters.
- Accuracy: 82.542%
- Benefits:
- Specialized in handling spatial meteorological data, such as grid-based information.
- Automatically learns hierarchical features, accommodating diverse scales.
- Benefits:
- Simple and interpretable model for understanding linear relationships.
- Offers insights into the significance of individual meteorological parameters.
This project is licensed under the MIT License. See the LICENSE file for details.