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Edge Node Machine Fault Prediction System by kruthikapappala is a document available to read on EtoBox.

The document presents a project report on developing an edge node solution for machine fault prediction, focusing on predictive maintenance for electric motors using machine learning and real-time data acquisition. The project aims to minimize downtime and repair costs by utilizing deep learning models on STM32 microcontrollers for early fault detection. The report includes a methodology, literature survey, and acknowledgments, highlighting the project

Author
kruthikapappala
Language
EN