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# Building a Predictive Maintenance Plugin with the InfluxDB 3 Processing Engine

**[InfluxData](https://daily.dev/sources/influxdb)** · 17 min read · 0 upvotes · 0 comments

## Summary

A step-by-step guide to building a predictive maintenance system using InfluxDB 3 Core's Processing Engine. The tutorial covers installing InfluxDB 3 Core, loading NASA's C-MAPSS turbofan engine degradation dataset, and writing a Python plugin that runs embedded in the database to estimate Remaining Useful Life (RUL) for each engine. The plugin computes a degradation health index from sensor readings, writes RUL estimates back to the database, and automatically raises maintenance alerts when engines cross a configurable danger threshold. Key concepts include the plugin model (scheduled, data-write, and HTTP-request triggers), using LineBuilder to write points from within a plugin, passing tunable parameters via trigger arguments, and iterating on plugins without recreating triggers.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.influxdata.com/blog/predictive-maintenance-plugin-tutorial>

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---

Tags: [#python](https://daily.dev/tags/python), [#data-science](https://daily.dev/tags/data-science), [#iot](https://daily.dev/tags/iot), [#influxdb](https://daily.dev/tags/influxdb)

[View this post on daily.dev](https://daily.dev/posts/building-a-predictive-maintenance-plugin-with-the-influxdb-3-processing-engine-83u9wij8t)

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