Alertifire Object Detection Dataset and Pre-Trained Model by ALERTIFIRE

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Here are a few use cases for this project:

Fire Safety Inspection: Alertifire can be used by health and safety inspectors in commercial kitchens, warehouses, and industrial environments. It can be trained to autonomously identify and rank potential fire hazards based on their level of severity, guiding inspectors to the most serious issues first.
Surveillance in High-Risk Industry: In industries such as chemical manufacturing or oil and gas extraction, where flammable liquids are frequently used, Alertifire can extend the capacity of human monitoring systems, proactively identify risks and alert relevant personnel about any detected changes that could lead to a fire.
Insurance Assessments: Insurance professionals can use Alertifire to assess the level of risk present in clients' properties or workplaces. It could help inform their decisions about premium rates and suggest mitigation measures.
Worker Training: In industries where fire hazards are common, Alertifire could be used in training modules to help workers learn how to identify and respond to various types of fire hazards.
Fire Prediction in Smart Homes: Alertifire could be integrated into home-based IoT networks to predict fires. It could identify low, medium, and high-risk equipment or materials and send alerts to homeowners or emergency services if a potential fire risk is detected.

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{ alertifire-t9twf_dataset,
    title = { Alertifire Dataset },
    type = { Open Source Dataset },
    author = { ALERTIFIRE },
    howpublished = { \url{ https://universe.roboflow.com/alertifire-y9dzw/alertifire-t9twf } },
    url = { https://universe.roboflow.com/alertifire-y9dzw/alertifire-t9twf },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { may },
    note = { visited on 2023-12-06 },
}