The Internet of Things on AWS – Official Blog

Category: AWS IoT Analytics

Get Started with the IoT Foundation Series from AWS Training and Certification

The IoT Foundation Series, a new curriculum dedicated to IoT on AWS, is now available online on the AWS Training and Certification website. This curriculum contains self-directed online training classes that are scenario-based and aligned with the library of IoT design patterns called the IoT Atlas and IoT best practices in AWS whitepapers. This curriculum […]

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Using AWS IoT Analytics to Prepare Data for QuickSight Time-Series Visualizations

Introduction Visualizing IoT data that can vary significantly over short periods of time (seconds) is important for several reasons: exploration and discovery of patterns, assessing trends and cyclicity, as well as observing potential correlations and anomalies. Insightful time-series visualizations can help identify anomalies, raise alerts based on these anomalies, and improve communication between various stakeholders, […]

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Introducing AWS CloudFormation support for AWS IoT Analytics

AWS CloudFormation support for AWS IoT Analytics resources was launched on December 18th, 2018. In this blog post, we introduce conventions for building IoT Analytics projects using CloudFormation and provide an array of sample templates to help you get started. As a refresher, every AWS IoT Analytics project has three required resources for data ingestion, […]

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AWS IoT Analytics Oil and Gas Customer Use Case

Our oil and gas customer wanted to deploy AWS IoT Analytics to help them:  Better understand their assets in the field (for example, pumps, generators, valve assemblies, and so on).  Derive actionable insights from their data.  Build a predictive maintenance solution to help reduce their costs. By using IoT Analytics, our customer can: Pre-process the […]

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Using AWS IoT for Predictive Maintenance

The interest in machine learning for industrial and manufacturing use cases on the edge is growing. Manufacturers need to know when a machine is about to fail so they can better plan for maintenance. For example, as a manufacturer, you might have a machine that is sensitive to various temperature, velocity, or pressure changes. When […]

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