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To implement the prototype, we leveraged the edge computing platform provided by MobiledgeX. It gives us a convenient way to deploy a containerized application to an edge infrastructure nearby. We deployed an open-source face recognition at the edge. We then implemented a Python program on a laptop to make it function as a video surveillance camera by using its webcam. The laptop keeps capturing the pictures, sending them to the edge, and calling the face detection algorithm to count the people in the room. If the occupancy is higher than a certain threshold, the image is sent to the cloud and stored. Otherwise, the program drops the image to protect residents’ privacy.
During the final review and judging phase, judges and audiences gave a lot of helpful comments and feedback. We together discussed topics like the scenarios that edge infrastructure is trusted, the capability of enhancing this application using trusted hardware, and how to extend this use case to other situations like controlling the activation of voice assistants.
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