Forest Fire Detection Object Detection Dataset and Pre-Trained Model by AUIC

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Explore Dataset

Here are a few use cases for this project:

Early Warning Systems: This model can be integrated into early warning systems for forest departments and fire brigades to promptly detect and counter forest fires, potentially saving thousands of acres of forest and the species that inhabit it.
Surveillance Drones: Drones equipped with this model can patrol forests and provide real-time updates on potential fire situations, enabling swift remedial actions.
National Park Surveillance: This model can help park rangers and other officials monitor forest areas within the park for signs of fire, helping ensure the safety of visitors and wildlife.
Environmental Research: Researchers studying climate change or forest ecosystems can use this model to detect and examine the frequency/resilience of certain areas against forest fires.
Insurance Claims Verification: This model can aid insurance agencies in quick verification of claims related to forest fires, speeding up the compensation process for those affected.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            forest-fire-detection-0trlx_dataset,
                            title = { Forest Fire Detection Dataset },
                            type = { Open Source Dataset },
                            author = { AUIC },
                            howpublished = { \url{ https://universe.roboflow.com/auic-84pzw/forest-fire-detection-0trlx } },
                            url = { https://universe.roboflow.com/auic-84pzw/forest-fire-detection-0trlx },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { nov },
                            note = { visited on 2024-06-26 },
                            }