An approach to more ergonomic and healthy lifestyles with hazardous pose detection
One of the leading causes of worker injuries is ergonomics, where factory workers, construction workers, and even regular staff put themselves at risk when they move heavy equipment or materials. Since our team has experience in machine learning, we wanted to see if there was a way we could harness the power of computer vision and machine learning to detect these high risky poses and alert workers when they perform them so they can continue to live happy healthy lives.
Build a model that is able to detect hazardous poses such as lifting items overhead, bending over, etc. in real time.
We used PoseNet from ml5.js for pose detection and we used p5.js for marking the specific keypoints and drawing the skeleton. We used machine learning for detecting potentially dangerous poses and notifying the person.
- PoseNet model
- JavaScript
- HTML
- CSS