Lifeline Detection Object Detection Dataset and Pre-Trained Model by Seoul National University

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Here are a few use cases for this project:

Construction Site Safety: The Lifeline Detection model can be used to monitor construction sites, ensuring that workers are adhering to safety guidelines including wearing hardhats and harnesses while on duty. It can alert supervisors if a worker is spotted without the necessary safety gear or if the lifeline is not properly secured.
Training and Education: Videoclips with annotations detected by this model could be used in safety training programs for construction workers. This can help illustrate the importance of various safety measures, such as wearing hardhats, securing lifelines, and more.
Accident Investigation: In the event of an accident at a construction site, the model can analyze footage to help determine whether necessary safety procedures were followed. This could assist in figuring out what went wrong and potentially help prevent similar incidents in the future.
Insurance Claim Verification: Insurance companies could use this model to validate claims related to work-related accidents or injuries on construction sites. This can help identify insurance fraud if it appears workers were not following standard safety protocols.
Remote Worksite Monitoring: For companies that have construction projects in remote locations, the model can be used to remotely monitor the site ensuring all safety protocols are being followed, including appropriate gear usage and lifeline attachment.

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.

YOLOv5

This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, state-of-the-art real-time object detection model.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            lifeline-detection_dataset,
                            title = { Lifeline Detection Dataset },
                            type = { Open Source Dataset },
                            author = { Seoul National University },
                            howpublished = { \url{ https://universe.roboflow.com/seoul-national-university-xqaz2/lifeline-detection } },
                            url = { https://universe.roboflow.com/seoul-national-university-xqaz2/lifeline-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { mar },
                            note = { visited on 2024-04-29 },
                            }