Pyronear provides an open‑source, low‑tech system that automatically detects early signs of forest fires using AI algorithms on low‑power micro‑computers attached to existing high‑point cameras. The solution continuously analyses video feeds, sends real‑time alerts to a cloud database and firefighter dashboard, and offers a modular, energy‑efficient design with openly shared code and datasets for cost‑effective deployment by forest agencies and fire services.
Funding
Funding not disclosed
Founders
Product
Problem
Forest fires often go undetected until they have grown large, delaying response from firefighting services and increasing ecological and economic damage. Limited monitoring resources and reliance on manual observation make early detection difficult, especially in remote or extensive natural areas.
Solution
Pyronear offers an open‑source, low‑tech system that automatically detects the onset of forest fires using AI algorithms running on micro‑computers connected to existing high‑point cameras. The system continuously analyzes video feeds, generates alerts when fire signatures are identified, and sends these alerts to a central database and supervision platform accessible by fire services. By leveraging open data and community‑driven development, Pyronear provides a cost‑effective, energy‑efficient solution that can be deployed with minimal new hardware and integrates with existing monitoring infrastructure.
Target Audience
Primary users are forest management agencies, fire protection services, and environmental NGOs that require automated, early‑warning fire detection across large natural areas.
Features
- AI‑based fire detection algorithm optimized for low‑power micro‑computers
- Compatibility with existing surveillance cameras positioned on elevated sites
- Real‑time alert transmission to a cloud‑hosted database and firefighter supervision dashboard
- Open‑source codebase and openly shared annotated image dataset for community improvement
- Energy‑sober hardware design enabling deployment in remote locations with limited power supply
- Modular architecture allowing integration with other systems such as NexSIS or custom monitoring tools