As enterprises and consumers increasingly adopt machine-learning-enabled smart cameras, these end-users’ expectations are becoming more sophisticated. In particular, smart camera users increasingly expect their deployed cameras to improve over time–for example, becoming more accurate and gaining new features. Traditionally, however, smart cameras that run machine learning at the edge have been difficult to upgrade. In this talk, we’ll explain how a cloud-native approach for running machine learning software at the edge enables smart camera developers to easily deploy improved models and new capabilities into existing, installed cameras. We’ll use application examples to illustrate the benefits of a cloud-native approach.
Sparking the Next Generation of Arm-Based Cloud-Native Smart Camera Designs
Session Speakers
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Stephen Su
Senior Product Manager, Arm, Inc.
Stephen Su is a Senior Product Manager in Arm’s IoT Line of Business group, based in San Jose, California. In his current role, he focuses on strategy and growth in smart camera and IoT segments. Stephen has supported and led Arm’s worldwide customer activities for over 15 years in image signal processor (ISP), microcontoller and CPU technical support, design wins, business development and OEM and silicon partner engagement. Stephen also manages Arm’s Mali-ISP product family, including the Mali-C55, Mali-C52, Mali-C32 and Mali-C10. He is an expert on the use of Arm’s CPUs, ISPs, NPUs and PSA (the Platform Security Architecture) as applied to surveillance, security, industrial, and smart home markets.
