fire _rooster Computer Vision Project
Updated 2 years ago
Metrics
Here are a few use cases for this project:
-
Wildfire Monitoring: This model can be employed for early wildfire detection and tracking. By identifying and classifying fire-starting areas at an early stage, preventive measures can ensure that the fire can be controlled more effectively.
-
Firefighting and Emergency Response Applications: The model can be used by firefighting departments or emergency services to enhance their ability to quickly detect fire or clear regions in live CCTV feeds, drone footage, or satellite images. This can greatly reduce response times and improve the efficiency of resource allocation.
-
Safety in Industrial Facilities: The model can be used to continually monitor high-risk industrial areas like oil refineries or hazardous chemical plants, where early detection of fire can prevent large scale disasters. It can send alerts to the control team as soon as a fire is detected.
-
Residential Security Systems: The model can be incorporated into home security systems to detect fires and alert homeowners, property managers, or security services. This can help mitigate damages and save lives in case of fires.
-
Environmental Research: The model can be used by environmental researchers for studying fire-associated trends and patterns, assessing damage caused by forest fires, and monitoring post-fire recovery of vegetation.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
fire-_rooster_dataset,
title = { fire _rooster Dataset },
type = { Open Source Dataset },
author = { fyp },
howpublished = { \url{ https://universe.roboflow.com/fyp-ersh3/fire-_rooster } },
url = { https://universe.roboflow.com/fyp-ersh3/fire-_rooster },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { may },
note = { visited on 2024-11-23 },
}