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Machine Learning applied to electric current pattern identification and classification of devices connected to an electric network.

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hervengassop/ElectricCurrentRecognition

 
 

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Electric Current Recognition

Machine Learning applied to electric current pattern identification and classification of devices connected to an electric network.

  • Description:

    Project, implement and evaluate a new model of energy monitoring in local networks based on electric current patterns detection, using embedded systems to capture current signals from the electrical network and machine learning to detect current patterns in electric circuits with objective to generate information from the collected and analysed data to optimize local energy consumption.

  • General objective:

    From a single data collector device, recognize devices connected to the electrical network and thus achieve a high level of energy monitoring for a low cost of infrastructure.

  • Requirements:

    • Python 3+
    • Jupyter Notebook
    • Pandas
    • Sci-Kit Learn
    • Numpy
    • Matplotlib
    • Arduino UNO
    • ACS712 - 5A
    • ACS712 - 30A

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Machine Learning applied to electric current pattern identification and classification of devices connected to an electric network.

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  • Jupyter Notebook 100.0%