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DC Motor Anomaly Detection System based on Arduino Solution

This Arduino-powered solution implements an energy monitoring-based anomaly detection system using a current sensor and machine learning models running on edge devices. By capturing the electricity flowing in and out of a machine, it can collect large amounts of data on energy usage patterns over time. This data is then used to train a machine learning model capable of identifying anomalies in energy consumption behaviors and alerting operators to potential issues. The solution offers a cost-effective and scalable method for maintaining equipment health and maximizing energy efficiency, while also reducing downtime and maintenance costs.
av-dh-design-subcategory CATEGORYav-dh-design-subcategory
Energy,Hardware,Software,Interconnect Passives & Electromechanical,Embedded,Sensors,Industrial,Machine learning,Programmable logic
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MFGR PART# BLK NM

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IMPORTANT NOTICE AND DISCLAIMER: AVNET PROVIDES THESE DESIGN FILES “AS IS” AND WITH ALL FAULTS, AND DISCLAIMS ALL WARRANTIES, EXPRESS AND IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR NON-INFRINGEMENT OF THIRD PARTY.  SEE LEGAL NOTICES | AVNET EMEA FOR ADDITIONAL INFORMATION.

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