EcoSentry is a real-time wildfire risk prediction and alerting platform powered by satellite data, AI, and geospatial analytics. It's designed to help governments, emergency responders, NGOs, and citizens take preemptive action before disaster strikes.
Every year, wildfires cause widespread destruction—impacting lives, biodiversity, and the global environment. Early detection and a rapid, informed response are absolutely critical to minimizing the catastrophic damage these fires can cause.
EcoSentry addresses this challenge by combining satellite intelligence with a powerful AI engine to provide timely, accurate alerts and actionable insights. Our system analyzes vast amounts of geospatial and weather data in real-time to predict high-risk zones, enabling preemptive action.
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- Real-time Wildfire Risk Prediction: Utilizes machine learning models to forecast potential fire outbreaks.
- AI-Powered Data Analysis: Processes complex satellite imagery (from MODIS, Sentinel-2, etc.) and meteorological data.
- Interactive Risk Maps: Provides a user-friendly geospatial visualization of high-risk areas.
- Instant Alerts: Delivers immediate notifications via SMS and a live dashboard to stakeholders.
- Multi-Threat Detection: Capable of identifying risks beyond fires, such as deforestation.
- Seamless Integration: Designed to connect with emergency response agencies and NGOs.
EcoSentry is built with a modern, scalable tech stack to handle real-time data processing and analysis efficiently.
| Layer | Technology Used |
|---|---|
| Frontend | HTML, CSS, JavaScript, React |
| Backend/API | Python, FastAPI |
| AI/ML Engine | TensorFlow, Scikit-learn, Pandas, NumPy |
| Satellite Data | Google Earth Engine, FIRMS, MODIS, Sentinel-2 |
| Cloud & DevOps | Google Cloud Platform (GCP), Firebase, Docker, Git, GitHub |
| AI Assistant | Gemini API |
Our platform heavily leverages the power and scalability of Google's ecosystem:
- Google Earth Engine: To access, process, and analyze multi-temporal satellite data.
- Firebase: For our real-time database, user alert history, and authentication.
- Google Cloud Functions: To handle alert triggers and scheduled data processing jobs.
- Google Cloud Storage: For storing satellite data snapshots and system logs.
- Gemini API: To enable natural language interaction, allowing users to query risks and get explanations.
- Google Cloud Platform (GCP): Serves as the infrastructure backbone for compute, AI model deployment, and database hosting.
To get a local copy up and running, follow these simple steps.
- Clone the repository:
git clone https://github.com/your-username/ecosentry.git
- Navigate to the project directory:
cd ecosentry - Install the required dependencies:
pip install -r requirements.txt
- Run the application:
uvicorn main:app --reload