A Demonstration of Smart Doorbell Design Using Federated Deep Learning

• URL: http://arxiv.org/abs/2010.09687v1
• Date: Mon, 19 Oct 2020 17:22:34 GMT
• Title: A Demonstration of Smart Doorbell Design Using Federated Deep Learning
• Authors: Vatsal Patel and Sarth Kanani and Tapan Pathak and Pankesh Patel and Muhammad Intizar Ali and John Breslin
• Abstract summary: This paper showcases the ability of an intelligent smart doorbell based on Federated Deep Learning. It can deploy and manage video analytics applications such as a smart doorbell across Edge and Cloud resources.
• Score: 0.09786690381850353
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Smart doorbells have been playing an important role in protecting our modern homes. Existing approaches of sending video streams to a centralized server (or Cloud) for video analytics have been facing many challenges such as latency, bandwidth cost and more importantly users' privacy concerns. To address these challenges, this paper showcases the ability of an intelligent smart doorbell based on Federated Deep Learning, which can deploy and manage video analytics applications such as a smart doorbell across Edge and Cloud resources. This platform can scale, work with multiple devices, seamlessly manage online orchestration of the application components. The proposed framework is implemented using state-of-the-art technology. We implement the Federated Server using the Flask framework, containerized using Nginx and Gunicorn, which is deployed on AWS EC2 and AWS Serverless architecture.

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