Forest fires are a cause for great concern to both the ecosystem, wildlife and human settlements. Their destructiveness depends on speedy detection and rapid response. Our IoT-based forest fire detection system stands as a compelling demonstration of an architecture for early fire detection in forested areas. By integrating sensors, data analytics, and real-time alerts via Telegram, the system showcases a path towards quick identification of potential fires. Grafana's data visualization enhances decision-making by offering clear insights into environmental conditions.
Project developed for the Software Engineering for Internet of Things course - University of L'Aquila.
Here are things you need to have on your computer beforehand.
- Docker
- Clone the repo
git clone https://github.com/AzimovS/iot-forest-fire-detection
- Run the containers
docker-compose up
- Navigate to http://localhost:3000/, where you can see the dashboard. Use the following credentials: username=admin, password=admin.
The configuration of the system is mainly contained in the docker-compose.yml file. Be sure that all the exposed mapped ports are free on your environment:
- 1883 and 9001 for Mosquitto MQTT Broker
- 8086 for InfluxDB
- 1886 for Node-RED
To interact with InfluxDB, navigate to http://localhost:8086/. Use the following credentials: username=admin, password=admin123.