Automate Safety and Security Procedures for Pipelines and Rigs

Increase Productivity While Improving Safety

Optimize business operations by deploying computer vision to monitor pipelines and safety procedures
A worker, wearing safety gear, inspecting systems in an oil processing facility.

Quickly Detect Component Malfunctions

Using images and video streams you may already have, computer vision can quickly alert you to environmental changes around your pipeline, as well as degraded components of your pipeline. Get early warning signals to avoid much larger production and environmental issues.

Protect Your Workforce

Trained computer vision models can help ensure proper safety processes and procedures are being met at all times, such as employing PPE detection throughout the workday.

Produce a Trained Model in Hours, Not Weeks

Roboflow seamlessly integrates with the most popular labeling services and training tools
Roboflow computer vision cycle

Continuously Improve and Scale Your Model After Implementation

As a centralized management tool for your datasets, Roboflow allows you to deploy your model and scale it as you collect more data. Easily detect and categorize types of defects, adjust configurations, and experiment with different labeling and training services.

Improve Model Quality With Less Data

Roboflow is specifically designed to create more accurate computer vision models using fewer images
Slice your high-resolution images up into smaller images. This preprocessing step makes it easier for your model to detect small objects, patterns, or fine details. Crucial information when it comes to classifying defects by type and severity.
Version Control
Dataset versions allow you to conduct rapid experimentation with various labeling and training tools. Adjust settings, generate export, and go.
Create more training data without uploading more images. Improve model accuracy from different angles or views by generating skewed or distorted versions of your source images.
Advanced Health Check
Helpful charts that provide insight into the quality of your dataset and how to improve it, including a breakdown of class balance, dimension insights, and an annotation heatmap.