How Atos Uses Computer Vision to Monitor Office Occupancy

Atos, a global leader in digital transformation, developed a privacy-first computer vision system using Roboflow to monitor office occupancy by counting entrants and exits via security camera feeds. This system, designed to run on the NVIDIA Jetson Nano, operates entirely on the edge, ensuring privacy by anonymizing data and recognizing people only as pixel shapes without identifying individuals. Atos leveraged Roboflow's end-to-end platform to efficiently build, train, and deploy the model within 60 days, using only 800 annotated images and data augmentation techniques to enhance model accuracy. The company compared its system with Microsoft's Azure Custom Vision, finding that Roboflow offered better developer experience, model confidence, and ease of deployment. The system uses active learning to improve continually, collecting data in real-time and incorporating it back into the model for ongoing enhancements, demonstrating the potential for applications beyond COVID-19 safety, such as at sporting events and retail environments.

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