System health monitoring
The starter kit provides a reference implementation for system health monitoring use cases. The solution is designed to reliably evaluate system health and detect anomalies in a large number of IoT metrics received from multiple sensors and machines.
Multiple system types
The starter kit includes a design guide that helps determine the right model type based on the properties of the monitored system and availability of the labeled data.
Power of Vertex AI AutoML
The starter kit leverages native Vertex AI AutoML components to evaluate system health. AutoML sharply reduces the feature and model engineering efforts, enabling developers to focus on more business-oriented problems.
We use only native Google Cloud services and open source libraries, so the starter kit can be easily extended and customized.
- Defect detection
- Anomaly classification
- Remaining useful life estimation
- Predictive maintenance
Monitor equipment health and prevent downtimes.
Continuosly control the product quality and detect anomalies.
Get the most value from your smart grid investments.
Implement sensor-based tank monitoring and asset monitoring.
Monitor electric vehicles and optimize EV charging.
Monitor production processes, ensure quality and compliance.
Why develop an IoT analytics solution in Google Cloud?
Google Cloud provides a powerful platform for creating smart manufacturing solutions that includes data processing, model development, and service deployment capabilities.
Google Cloud provides native capabilities for IoT data collection, deployment on edge servers, and two-communication with devices. These services help sharply reduce development and maintenance costs.
The implementation of smart manufacturing and IoT analytics capabilities requires a powerful ML platform that supports data preparation, model development, model serving, and many other functions. Google Cloud is at the forefront of cloud computing services.
How it works
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