Early Forest Fire Detection

Context

Pyronear offers a holistic solution for managing fire risks. Central to its capabilities is an innovative early wildfire detection algorithm, seamlessly operated on a compact microcomputer. This core system is augmented by a network of high-resolution cameras strategically positioned at elevated vantage points, providing panoramic coverage of forested regions. Together, these components form a resilient and proactive strategy for wildfire prevention and management.

Our detectors communicate fire alerts to a database that is connected to a supervision platform for the fire department.

– Pyronear

Overview of the Pyronear system to monitor forests around the clock

Forests Protection

Protecting forests from fire is crucial for several reasons:

• Biodiversity Conservation: Forests are home to a vast array of plant and animal species. Wildfires can devastate habitats, leading to the loss of biodiversity and potentially driving species to extinction.
• Carbon Sequestration: Forests act as carbon sinks, absorbing carbon dioxide from the atmosphere and storing it in trees and soil. When forests burn, this stored carbon is released back into the atmosphere, exacerbating climate change.
• Water Resources: Healthy forests play a critical role in regulating water cycles. They help maintain soil moisture, reduce erosion, and sustain the flow of rivers and streams. Wildfires can disrupt these processes, leading to soil degradation and affecting water quality and availability.
• Economic Impact: Forests provide various ecosystem services, including timber, non-timber forest products, and recreational opportunities. Wildfires can damage these resources, impacting industries such as forestry, tourism, and agriculture, leading to economic losses for communities.
• Human Health: Wildfires produce smoke and air pollution, which can pose significant health risks, especially to vulnerable populations such as children, the elderly, and individuals with respiratory conditions. Protecting forests from fire helps safeguard public health and well-being.

Overall, preserving forests from fire is essential for maintaining ecological balance, mitigating climate change, sustaining livelihoods, and safeguarding human health and biodiversity.

Project Scope and Objectives

Our partnership is focused on enhancing the precision of the early forest fire detection system, with the goal of minimizing false alarms to bolster confidence among firefighters and stakeholders. Additionally, we aspire to incorporate industry-leading methodologies for effectively managing, deploying, and maintaining Machine Learning Models, ensuring optimal performance and reliability over time.

Overview of the camera system that can cover 360 degrees angle

Our work is centered on enhancing the core of the Pyronear system, which analyzes real-time images from cameras mounted on tower antennas.

Overview of the embedded ML system

Setting up the Pyronear system

In this section, we detail the setup of the Pyronear system in Fontainebleau before the summer of 2024. This pilot project, initiated by the fire department, aims to evaluate Pyronear’s effectiveness in detecting early forest fires.

By placing cameras on top of tower antennas, the system can monitor the surrounding forest over a long range, detecting fires from tens of kilometers away.

The image below shows the antenna where the Pyronear system is installed.

Two cameras are mounted on top of the antenna tower, providing 360-degree coverage of the area. These cameras can be programmed to capture images at specific angles.

The map below illustrates how the chosen set of angles enables complete 360-degree coverage.

Range covered by the two cameras by taking pictures at different angles

From the top of the antenna, the forest can be observed over a vast distance, allowing a single Pyronear system to effectively monitor and protect a large area. In practice, antennas are often positioned on hills, enabling the detection of forest fires from 30 to 60 kilometers away.

Shown below is the installed Pyronear system, housed in a secure enclosure. The Pyronear team developed a plug-and-play setup featuring a central processing unit built around a Raspberry Pi, connected to four cameras that provide 360-degree coverage. This system processes images continuously, around the clock.

The computer vision model detected a forest fire in Fontainebleau from a distance of 35 kilometers in real time, setting a new record for the Pyronear system. The video below shows a thin black smoke rising in the distance.

Conclusion

In summary, an advanced computer vision model for detecting early signs of forest fires provides a cost-effective and efficient means of safeguarding our forests. This technology facilitates the swift deployment of firefighters, greatly improving our capacity to protect forests that are increasingly threatened by the impacts of global warming.

One can try out the model from the ML Space or directly from the snippet below: