“A Mask Detection Smart Camera Using the NVIDIA Jetson Nano: System Architecture and Developer Experience,” a Presentation from BDTI and Tryolabs

Evan Juras, Computer Vision Engineer at BDTI, and Braulio Ríos, Machine Learning Engineer at Tryolabs, co-present the “A Mask Detection Smart Camera Using the NVIDIA Jetson Nano: System Architecture and Developer Experience” tutorial at the May 2021 Embedded Vision Summit.

MaskCam is a prototype reference design for a smart camera that counts the number of people wearing masks in its field of view and reports statistics to the cloud. Based on the Nvidia Jetson Nano, all AI processing is handled on the device. In this presentation, BDTI and Tryolabs share their story of developing MaskCam, and how the two companies went from concept to working prototype with a small team in just a few months.

Juras and Ríos explain the hardware and software design of the camera and present their companies’ experiences working with Jetson Nano (both the Dev Kit and the system-on-module), NVIDIA’s DeepStream framework and containerization via balenaOS/balenaCloud. The solution features a custom tracking component, static video file serving, video streaming over RTSP, and MQTT communication to report statistics and receive commands using a web interface. Working with Jabil Optics, Juras and Ríos also present estimated manufacturing costs for volume production.

See here for a PDF of the slides.

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