Real-Time Process Tracking with Computer Vision

Aarnav Shah discusses the development of a real-time handwashing steps-tracking system using computer vision and a Python application integrated with a Roboflow-trained model, aimed at ensuring proper hand hygiene in healthcare, food service, and general business environments. The project involves creating a handwashing step recognition model by collecting and annotating images of eight distinct handwashing steps, training the model using Roboflow's tools, and deploying it for real-time use with a Python-based graphical user interface (GUI) built with OpenCV. The system provides instant feedback by tracking the duration of each step, encouraging users to perform them correctly for at least a minimum amount of time. The visual interface offers progress bars for each step, motivating users by showing when all steps have been satisfactorily completed. This innovative approach not only supports compliance with health protocols but also enhances public safety by reducing the risk of infections and contamination.

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