Amazon Lookout for Equipment is no longer available to new customers as of October 17, 2024. For alternatives we recommend exploring our blog post.

« Machine Learning

Amazon Lookout for Equipment

Avoid unplanned downtime by automatically detecting abnormal equipment behavior

Use data from existing sensors to create machine learning (ML) models specific to your equipment.

Respond with speed and precision with automatic equipment monitoring that pinpoints anomalous sensors.

Accelerate issue resolution with immediate notifications and automatic actions when anomalies are detected.

Improve model performance and accuracy of alerts by incorporating anomaly trends and feedback.

How it works

Amazon Lookout for Equipment is an ML industrial equipment monitoring service that detects abnormal equipment behavior so you can act and avoid unplanned downtime.

Diagram shows how Lookout for Equipment uses historical data and maintenance records to automatically detect anomalies in your equipment.
What is Amazon Lookout for Equipment? (1:44)
Why Lookout for Equipment?
Lookout for Equipment automatically analyzes sensor data for your industrial equipment to detect abnormal machine behavior. This allows you to detect equipment anomalies with speed and precision, quickly diagnose issues, and act to avoid unplanned downtime, with no ML experience required.
Why Lookout for Equipment?
Lookout for Equipment automatically analyzes sensor data for your industrial equipment to detect abnormal machine behavior. This allows you to detect equipment anomalies with speed and precision, quickly diagnose issues, and act to avoid unplanned downtime, with no ML experience required.

Use cases

Detect generator shutdowns

Accurately monitor sensor data on flow rates, temperature, pressure, and oxygen levels and get alerts to avoid untimely shutdowns.

Identify abnormal machine behavior

Analyze historical maintenance and sensor data about RPMs, flow rates, temperature, pressure, and vibration to learn trends.

Improve alert accuracy over time

Enhance model performance and alert accuracy by incorporating human feedback on anomalies and learning predicted operational usage trends.

Customers

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