Extract sensor data and apply object detection with custom business logic - Scene Intelligence with Rosbag on AWS

Extract sensor data and apply object detection with custom business logic

Publication date: November 2023 (last update: May 2024)

Scene Intelligence with Rosbag on AWS provides an end-to-end solution for extracting sensor data from rosbag files generated from autonomous driving use cases. This solution guides users through a sample use case to demonstrate how the processing occurs and where custom logic can be applied to the extracted data. You can use this solution to:

  • Stage sample rosbag files

  • Extract rosbag sensor data such as metadata and images

  • Apply object detection (YOLOv5) and lane detection (LaneDet) models to extracted images

  • Apply scene detection business logic and store the output in an indexable fashion, using Amazon DynamoDB and Amazon OpenSearch Service

This implementation guide provides an overview of the Scene Intelligence with Rosbag on AWS solution, its reference architecture and components, considerations for planning the deployment, and configuration steps for deploying the solution to the Amazon Web Services (AWS) Cloud.

The intended audience for using this solution's features and capabilities in their environment includes solution architects, business decision makers, DevOps engineers, data scientists, and cloud professionals.

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Know the cost for running this solution.

The estimated cost for running this solution in the US East (N. Virginia) Region is USD $605.13 per month for AWS resources.

Cost
Understand the security considerations for this solution. Security
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View or download the AWS CloudFormation template included in this solution to automatically deploy the infrastructure resources (the "stack") for this solution. AWS CloudFormation template
Access the source code and optionally use the AWS Cloud Development Kit (AWS CDK) to deploy the solution. GitHub repository