Projects / AI Innovation Challenge

Detecting Forest Wood Fire using IoT Sensor Data

Challenge Completed!

Omdena Featured image

50 AI engineers collaborated for 8 weeks to analyze sensor data and test possible systemic data models to develop an intelligent recognition algorithm to detect fire of different types of wood.

The project partner, Dryad Networks, is a Germany-based startup that provides ultra-early detection of wildfires as well as health and growth-monitoring of forests using solar-powered gas sensors in a large-scale IoT sensor network. Dryad aims to tackle wildfires, which are causing up to 20% of global CO2 emissions and have a devastating impact on biodiversity.

Dryad - Wildfire Detection Germany

The problem

The world’s forests are burning! If current trends continue, up to 170 million hectares could be lost until 2030 and with it, we gradually lose the earth’s great carbon sink consuming 110 billion metric tons of CO2.

The project outcomes

The project’s goal was to build an intelligent model that will detect fire of different types of wood through analysis of the existing sensor data, thereby enabling alarms for firefighters early enough, so they can extinguish it. During the period of eight (8) weeks, the team designed and implemented several data-based pipelines, leveraging the dataset provided by the Dryad team. Combing a massive and extensive analysis of the datasets provided, together with the state-of-the-art machine learning techniques, the team delivered the following.

The results of this project lie in the state of art machine learning models and correctly classify the sensor data into two categories, “in-smoke” and “clean-air”.  The model developed in this project is scalable and replicable. Such a solution has the potential to reduce forest fires, thereby enabling alarms for firefighters early enough, so they can extinguish them. This will ultimately help to achieve the sustainable development goals in the areas of life on land and climate action.

First Omdena Project?

Join the Omdena community to make a real-world impact and develop your career

Build a global network and get mentoring support

Earn money through paid gigs and access many more opportunities

Your benefits

Address a significant real-world problem with your skills

Get hired at top companies by building your Omdena project portfolio (via certificates, references, etc.)

Access paid projects, speaking gigs, and writing opportunities


Good English

A very good grasp in computer science and/or mathematics

Student, (aspiring) data scientist, (senior) ML engineer, data engineer, or domain expert (no need for AI expertise)

Programming experience with Python

Understanding of Data Analytics, Machine Learning, and/or Remote Sensing.

This challenge has been hosted with our friends at

Application Form

Related Projects

media card
Developing an AI-Driven Chatbot for Disaster Assistance and Emergency Relief
media card
Earthquake Quick Damage Detection using Computer Vision (Turkey-Syria Earthquake Data)
media card
Mapping Multi-Hazard Risk Areas and Identifying Optimal Response Routes

Become an Omdena Collaborator

media card
Visit the Omdena Collaborator Dashboard Learn More