Predictive maintenance is the process of using sensor data to detect the condition of equipment to determine when replacements are needed or when maintenance should be performed. Use real-time data for predictive maintenance and a proactive strategy to monitor the performance and condition of equipment by:
- Streaming real-time data from sensors
- Leverage inline computations to make predictions
- Stream prediction data to a BI tool to visualize results
InfinyOn Cloud makes predictive maintenance simple by collecting data from endpoints in any geo-location with fast and efficient single digit millisecond latency. Spin up a cluster, select source and sink connectors from our catalog, configure producers and consumers, then create a topic for streaming data. SmartModules can be set up in order to aggregate, filter or map streaming data. InfinyOn Cloud makes it simple to set up, deploy and manage your cluster.
Developers can use Fluvio open-source software that offers built-in packaging for multiple operating systems, from Raspberry PI to various Linux distributions. Support for the most common programming languages makes it easy to build custom connectors to virtually any server or data store for predictive maintenance.