Forest Fire Detection with IoT and Biophysical Indicators

This IoT system is a key component of the larger RAT-EOS-PC project (Activity A.3.3), which encompasses several initiatives focused on improving early fire detection across the Spain-Portugal cross-border region. For more comprehensive information about the overall project, please visit the main project site.

Project Overview

An integrated solution combining real-time sensor data and open-source platforms for forest fire management.

Our Mission

Deploy low-cost wireless sensors in high-risk zones like Sierra de Gata and Cáceres Centro. Detect fire outbreaks early and test regional scalability across Extremadura.

Our Technology

Apache Kafka, Mosquitto, Elasticsearch, Kibana, ElastAlert, N8N, and more ensure seamless real-time data flow, alerting, and visualization.

Sensors & Equipment

Includes Dragino weather stations, CO₂ monitors, soil sensors, and gateways—carefully deployed for localized data.

Program Funding

RAT_EOS_PC is 75% co-financed by the EU through the Interreg España–Portugal (POCTEP) 2021–2027 program to tackle climate challenges and improve early warning systems.

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Our platform

Our interactive dashboard provides clear and timely insights into forest fire risks and environmental conditions across Portugal and Spain.

Real-time Meteorological Data: Continuously updated to reflect live weather.
Geospatial Visualizations: Interactive maps displaying fire risk zones and sensor data.

Designed to support faster responses by authorities and communities, reducing the impact of forest fires through smarter early warning.

Access to our platform is restricted. To obtain credentials, please contact us.

Visit the Platform

Alert System

Our alerting system ensures that critical fire-related events and anomalies are detected and communicated in real time.

Automated Rule-based Alerts: Powered by ElastAlert to scan logs and metrics continuously.
Workflow Automation: n8n handles downstream actions like emails, SMS, and integration with third-party services.

This system reduces reaction times and ensures that both technical teams and field responders are instantly notified of potential threats or anomalies.

Standardized Data Model

Our project adopts a standardized approach for environmental sensor data representation, based on the globally recognized Smart Data Models initiative. This ensures consistency, interoperability, and long-term scalability.

The model facilitates easier data exchange, integration with external platforms, and streamlined analytics across multiple sources.

View Data Model Docs