cloudworker Object Detection Dataset and Pre-Trained Model by Junsung

Images

1801 images

Explore Dataset

Here are a few use cases for this project:

Safety Compliance Monitoring: In the construction field, this model can be used to monitor worker compliance with safety protocols on-site in real-time. It can identify if workers are wearing helmets, if they are engaged in unsafe behaviors such as climbing without a helmet or stepping on railings, and alert managers immediately.
Efficiency Analysis: Companies can use this model to study the efficiency of the workers. For instance, it could potentially identify how often workers are actively building, moving materials, or interacting with scaffolding, providing insights for potential efficiency improvements.
Accident Prevention and Investigation: The model can be used to predict potential accidents by detecting dangerous actions such as workers leaning out from the scaffolding or throwing materials, providing an opportunity to intervene before an incident occurs. It can also help in accident investigations by identifying the cause of accidents based on workers' actions.
Automated Construction Records: This model can help in creating automated construction logs which include when and how scaffolding was installed and dismantled, how workers interacted with it, how much material was used over time, etc., without the need for manual record-keeping.
Training and Education: Images labeled by this model can serve as a basis for developing education and training programs for new workers. They can help visualize best practices and safety precautions related to working with scaffolding.

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{
                            cloudworker_dataset,
                            title = { cloudworker Dataset },
                            type = { Open Source Dataset },
                            author = { Junsung },
                            howpublished = { \url{ https://universe.roboflow.com/junsung-lxlim/cloudworker } },
                            url = { https://universe.roboflow.com/junsung-lxlim/cloudworker },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-05-08 },
                            }