Wildfire Detection Computer Vision Project

FYDP

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Description

Here are a few use cases for this project:

  1. Early Wildfire Alert System: The model can be integrated into a digital monitoring network to analyze satellite or drone images. When it detects signs of wildfire, authorities are alerted early and can take proactive measures to control the damage.

  2. Safety Measures for Hiking/Camping: Apps catering to hikers or campers can use this model to provide real-time updates about areas affected by wildfires. This ensures tourists avoid dangerous areas, enhancing their safety in outdoor adventures.

  3. Insurance Claim Verification: Insurance companies can use this model to swiftly assess the validity of claims related to wildfire damage. By analyzing provided imagery, they can detect signs of fire, supporting fair and efficient claims processing.

  4. Environmental Research: Ecologists and climate scientists can use the model to study the frequency, intensity, and geographical spread of wildfires. This could contribute to research on climate change and inform strategies to manage resources.

  5. Real Estate Property Evaluation: This model can be used by real estate agencies or prospective property buyers to assess the risk of wildfires in a specific area. It can analyze historical geographical data to identify areas often affected by wildfires, informing purchase decisions and pricing.

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Cite This Project

LICENSE
CC BY 4.0

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

                        @misc{
                            wildfire-detection-iqlsm_dataset,
                            title = { Wildfire Detection Dataset },
                            type = { Open Source Dataset },
                            author = { FYDP },
                            howpublished = { \url{ https://universe.roboflow.com/fydp-c9t09/wildfire-detection-iqlsm } },
                            url = { https://universe.roboflow.com/fydp-c9t09/wildfire-detection-iqlsm },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-12-23 },
                            }
                        
                    

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