Welcome to the SWEEP Workflows repository by DotMote Labs, showcasing executable examples and workflow templates for use with the SWEEP platform — a cloud-native engine for geospatial and IoT data processing.
This repository contains demo workflows, task scripts, and Jupyter notebooks to help you prototype, test, and deploy automated pipelines on SWEEP.
SWEEP (Scalable Workflow Execution & Event Processing) is a serverless, graph-based engine that supports sensor-to-cloud automation for:
- Remote sensing pipelines
- IoT network integration
- Environmental & ecological monitoring
- Geospatial ML inference workflows
Workflows are defined declaratively as DAGs (Directed Acyclic Graphs), with each node performing a task and routing data to the next stage.
SWEEP-Workflows/
├── demo-workflows/
│ ├── landsat_ndvi/(coming)
│ ├── crop_health_monitoring/(coming)
│ ├── soil_moisture_alerts/(coming)
│ ├── coffee-berries
│ ├── meadows-demo
│ └── README.md (workflow-specific instructions)
├── notebooks/
│ ├── visualize_ndvi.ipynb
│ └── calibrate_sensors.ipynb
├── tasks/
│ ├── download_satellite.py
│ ├── compute_ndvi.py
│ └── push_to_s3.py
└── LICENSE
Each
demo-workflows/subfolder contains a complete, runnable DAG definition in SWEEP config JSON format, plus task references.
git clone https://github.com/SWEEP-Inc/SWEEP-Workflows.git
cd SWEEP-WorkflowsInstall Python dependencies if your task modules use any:
pip install -r requirements.txt # optionalTo launch a workflow:
- Log into your SWEEP dashboard
- Navigate to Workflows → Import
- Upload the JSON file from
demo-workflows/your-workflow/ - Customize parameters as needed
- Execute and monitor via the UI
- Landsat NDVI Computation: Triggered on new satellite data, calculates NDVI and sends alerts if vegetation health drops.
- Soil Moisture Monitoring: Pulls IoT sensor readings and alerts when moisture falls below thresholds.
- Sensor Calibration: Uses Jupyter notebooks to visualize and tune field sensor response curves.
We welcome contributions — whether it's a new example workflow, bugfix, or integration. Open an issue or submit a pull request.
This project is licensed under the MIT License.