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By Leslie Rodriguez, Raheel Zubairy | Published November 16, 2017
CloudIoTPlatform as a ServiceServerlessVision
Performing industrial equipment inspection can be time consuming, in some cases taking hours or weeks, especially when equipment is widely distributed for industries like oil and gas, transportation (roads and railways), construction, and agriculture.
This code pattern demonstrates how you can be automate this inspection by using images of the equipment to show the personnel which equipment requires attention, so that it can be fixed to meet normal equipment standards. The Watson™ Visual Recognition service can identify specific defects or whether the image meets normal conditions. The analysis of the image is triggered by IBM Cloud Functions as an image is added to a Cloudant® database.
In this code pattern, you use machine learning classification techniques to check industrial equipment for various damages using visual image inspection. Using Watson Visual Recognition, you’ll analyze the image against a trained classifier to inspect oil and gas pipelines with six identifiers: Normal, Burst, Corrosion, Damaged Coating, Joint Failure and Leak. For each image, you’ll receive a percent match for each of the identifiers based on how closely the image matches one of the damaged identifiers or the Normal identifier. This data can then be used to create a dashboard to show which pipelines require immediate attention or no attention. The image data is stored in a Cloudant database.
This code pattern demonstrates how IBM Cloud Functions can trigger a microservice as an image is added to the Cloudant database. The microservice performs the visual recognition analysis and updates the Cloudant database with the analyzed data.
In this code pattern, you learn how to:
Ready to put this code pattern to use? Complete details on how to get started running and using this application are in the README file.
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