Ensuring safe stones gather moss.
An open-source, decentralized environmental monitoring and slope-stability tracking network designed for remote, rugged terrain. Utilizing localized LoRaWAN mesh communication alongside EcoWitt meteorological sensors, the system aggregates real-time microclimate data, barometric pressure, and physical movement tracking.
At the core of the MOSSS physical tracking infrastructure is the Wake on Interrupt Landslide Detector (WOILD) subsystem—an open-source hardware and telemetry framework specifically engineered to monitor slope stability and ground acceleration.
All data streams converge on a centrally located, local Home Assistant Core gateway, which orchestrates automated mobile alerts via custom vector deviation matrices and bridges the network into broader commercial smart integrations.
All technical guides, hardware schematics, firmware source code explanations, and step-by-step deployment instructions are hosted in our interactive mdBook:
👉 Read the full Documentation: Modular and Open-Source Science Station (MOSSS)
- Chapter 1: Hardware & Bill of Materials – Component lists, enclosure assemblies, and pinouts.
- Chapter 2: Home Assistant Setup – Central gateway provisioning and data retention rules.
- Chapter 3: Home Assistant Integrations – HA Companion App, Native Integrations, Apps (Add-ons), HACS, and remote access options.
- Chapter 4: TTN, LoRa, and MQTT Data Transmission – SenseCAP gateway setup, TTN application routing, and MQTT bridges.
- Chapter 5: WOILD Edge Node Firmware – Wake-on-Interrupt Landslide Detector configuration and JavaScript payload decoders.
- Chapter 6: Field Deployment – Physical installation, tilt verification, and weather station calibration.
- Chapter 7: Troubleshooting & Maintenance
- Appendix - Credits, AI disclaimers, Copyright.
If you are browsing the repository directly on GitHub, use this directory map to quickly find files for your current build phase:
| What you want to do | Go to Directory | Description & Key Files |
|---|---|---|
| Build & Wire Hardware | /hardware |
Schematics (v3_circuit.png), PCB Gerbers, and enclosure guidelines. |
| Flash Firmware & Add Payload Decoder | /software |
Arduino sketch for WOILD v1.1.6 nodes, TTN JS decoder, and ESPHome YAMLs. |
| Configure Home Assistant & Alerts | /software/Home-Assistant |
HAOS deployment, databroker M2M user, template sensors, and recorder settings. |
| Read Notebooks & Field Research | /docs |
Science Station Notebook, field logs, and research documentation. |
| View Diagrams & Photos | /images |
Wiring diagrams, circuit photos, and dashboard UI captures. |
| Layer | Component / Device | Function / Specs |
|---|---|---|
| Field Nodes | Heltec WiFi LoRa 32 V3 | MPU6050 Accelerometer, DHT22, 1W Solar |
| Weather Array | EcoWitt WN90 & GW3001 | Piezo Rain, Anemometer, Temp/Humid/Pres |
| Gateways | SenseCAP M2 & EcoWitt | LoRaWAN (TTN), Local Webhooks / Wi-Fi |
| Core Gateway | Raspberry Pi 4 / 5 | Local Home Assistant Core server, Nabu Casa |
- Telemetry Collection: Solar-powered WOILD LoRa nodes monitor environmental metrics and structural movement on hillsides, remaining in deep sleep until periodic transmission or hardware motion interrupts trigger an uplink.
- Backhaul: Data is pushed via LoRaWAN to the SenseCAP gateway (integrated with TTN), while weather data routes through the EcoWitt gateway. Remote ESP32 Wi-Fi nodes utilize encrypted Tailscale WireGuard tunnels.
- Processing & Action: Home Assistant Core ingests all streams, evaluates slope movement against real-time rainfall data via custom matrix template equations, handles local valley logic, and pushes automated alerts to mobile clients.
- System Design & Architecture: Developed by Brandon J. Winters, Ph.D., Murphy O'Malley, and Evan Streeter.
- Firmware & Core Logic: Built on the WOILD v1.1.6 framework.
- Documentation & Asset Assistance: Portions of the configuration optimization, code documentation, and README organization were refined with the assistance of large language models.
- Visual Imagery: Conceptual diagrams, branding icons, or repository header graphics were generated using AI imaging tools for illustrative and repository-visual enhancement purposes.
If you are utilizing the WOILD framework, hardware PCB configurations, or the Home Assistant automation matrix in academic research, please cite the primary manuscript.
This project is open-source under the Creative Commons - Attribution - Share Alike 4.0 . Contributions, issues, and field feedback are welcome!