Rp FYP Med PPE Object Detection Dataset and Pre-Trained Model by Universiti Teknologi Malaysia

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Explore Dataset

Here are a few use cases for this project:

PPE Compliance Monitoring: This model can be used in healthcare units, factories, and labs dealing with hazardous substances to ensure staff compliance with Personal Protective Equipment (PPE) guidelines. It can automatically detect and alert if a worker is missing any PPE item.
Virtual PPE Training: The model can be integrated into virtual reality or augmented reality platforms to educate workers about the importance of each PPE item, how to wear it, and what constitutes a full set of PPE.
Supply Chain Management for PPE: The model can monitor the levels of PPE stocks in real-time by identifying the specific type of PPE in supply rooms. This would be valuable in maintaining adequate inventory levels, especially during health crises.
Remote Patient Care: The model can be used in telemedicine applications to ensure healthcare personnel are adequately dressed when administering at-home care to contagious patients.
Safety Analysis in Public Spaces: Used in CCTV or other surveillance systems, the model can assess the level of PPE compliance in public spaces, which may be important during infectious disease outbreaks or in areas with high air pollution.

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{ rp-fyp-med-ppe_dataset,
    title = { Rp FYP Med PPE  Dataset },
    type = { Open Source Dataset },
    author = { Universiti Teknologi Malaysia },
    howpublished = { \url{ https://universe.roboflow.com/universiti-teknologi-malaysia-y1eni/rp-fyp-med-ppe } },
    url = { https://universe.roboflow.com/universiti-teknologi-malaysia-y1eni/rp-fyp-med-ppe },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { jun },
    note = { visited on 2023-12-05 },
}