What does this Amazon Web Services Solution do?
The IP camera AI SaaS solution aims to empower the security industry by providing artificial intelligence capabilities in the cloud. It helps you reduce the time of work of model training, architecture, and model deployment, from many days to a few minutes. The solution currently provides three AI algorithm functions: face detection, human figure detection, and face comparison. With this solution, you can quickly deploy an end-to-end SaaS services in the Amazon Web Services, and your end users can easily use these AI functions through API calls.
Amazon Web Services Solution Overview

Architecture Description
Amazon API Gateway: API Gateway is responsible for routing customers HTTP POST requests and it offers custom domain binding. Meanwhile, API gateway also provide API key configuration to control the requesters' access authority.
Amazon Lambda: Lambda function routes HTTP POST request which contains input images with base64 format to SageMaker endpoint for inference and it dumps image and final response into S3 bucket for further performance check or data collection.
Amazon S3: S3 is used to store input requests and inferenced responses. The inferenced result can be used for next round of labelling, model training, parameter tuning, to increase the overall model performance.
Amazon SageMaker: SageMaker cluster handles customers inference request, the face detection, human body detection and face comparison models are loaded according deployment configuration. Sagemaker endpoints could be configured to auto-scaling according to requests' pattern to support high-concurrency application scenarios.
Note that the AI algorithms are packaged in Amazon ECR. You can choose the built-in AI algorithms or you could make althorithms of your own and then load , deploy and use them into this solution.
IP Camera AI SaaS Solution
Version 1.0.0
Last updated: 05/2021
Author: Amazon Web Services
Estimated deployment time: 20 min
Features
Easy to extend
Deploy as SaaS
Deploy features on demand

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