Discrete and continuous manufacturing lines generate a high volume of products at low latency, ranging from milliseconds to a few seconds. To identify defects at the same throughput of production, camera streams of images must be processed at low latency. Additionally, factories may have low network bandwidth or intermittent cloud connectivity. In such scenarios, you may need to run the defect detection system on your on-premises compute infrastructure, and upload the processed results for further development and monitoring purposes to the AWS Cloud. This hybrid approach with both local edge hardware and the cloud can address the low latency requirements and help reduce storage and network transfer costs to the cloud. This may also fulfill your data privacy and other regulatory requirements.
In this post, we show you how to detect defective parts using Amazon Lookout for Vision machine learning (ML) models running on your on-premises edge appliance.
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