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Guidance for Capturing Retail Video Analytics on AWS

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Overview

This Guidance shows how retailers can harness in-store cameras and AI/ML capabilities to gain deeper customer insights and enhance in-store experiences. With this Guidance, retailers can automatically collect valuable analytics like heatmaps, dwell-time, and traffic flow. This approach empowers brick-and-mortar retailers to better understand customer behavior, optimize layouts, and improve the shopping experience. By analyzing customers' in-store journeys, retailers can make data-driven decisions to enhance customer satisfaction, increase conversions, and boost overall sales performance.

How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

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Sample code

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Well-Architected Pillars

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

Integrating Amazon EC2 with Amazon CloudWatch logs allows you to seamlessly store and search your application logs, without additional infrastructure. Automatically scale your EC2 instances based on service events, such as new Amazon S3 objects or Amazon SQS messages. CloudWatch allows you to visualize and analyze these components so you can identify performance bottlenecks and troubleshoot requests.

Read the Operational Excellence whitepaper 

Use AWS Identity and Access Management (IAM) roles with minimum privileges to provide secure access to different components within your architecture. This approach ensures the best authorization mechanism to protect your system.

Read the Security whitepaper 

Amazon EC2 Auto Scaling groups provide resiliency in processing video files, while Amazon SQS helps ensure that files are processed by your frontend application running on Amazon EC2. As managed services, Amazon S3 and Amazon SQS offer inherent reliability, with Amazon SQS monitoring queue length to spin up additional EC2 instances and Amazon EC2 Auto Scaling health checks confirming that new instances are provisioned to maintain desired capacity.

Read the Reliability whitepaper 

Use Amazon EC2 GPU instances to satisfy the performance requirements of your video processing use case. Yolo9 deep learning models and GPU-based EC2 instances can help achieve optimal performance in your object detection algorithms.

Read the Performance Efficiency whitepaper 

The serverless nature of Amazon S3 and Amazon SQS eliminate the need for dedicated hosts when not in use. Amazon EC2 Auto Scaling groups and GPU-based instances optimize costs, as faster processing means less total compute time required compared to CPU-based instances.

Read the Cost Optimization whitepaper 

Serverless services and Amazon EC2 Auto Scaling groups in this Guidance help reduce power consumption and environmental impact by eliminating wasteful overprovisioning of compute resources. Services like Amazon SQS, Amazon S3, and Amazon EC2 Auto Scaling are managed by AWS and help minimize wasted compute resources.

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Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.