Alertifire Computer Vision Project

ALERTIFIRE

Updated 2 years ago

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Classes (12)
CommercialCookingEquipment_High
CommercialCookingEquipment_Low
CommercialCookingEquipment_Medium
FlammableLiquid_High
FlammableLiquid_Low
FlammableLiquid_Medium
LiveElectricalEquipment_High
LiveElectricalEquipment_Low
LiveElectricalEquipment_Medium
OrdinaryCombustible_High
OrdinaryCombustible_Low
OrdinaryCombustible_Medium

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Description

Here are a few use cases for this project:

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

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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{
                            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 2024-11-16 },
                            }
                        
                    

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