Application Software Pack: ML-Based System State Monitor

APP-SW-PACK-ML-STATE-MONITOR

Software Details

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Diagram

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ML-based System State Monitor - App SW Pack

ML-based System State Monitor - App SW Pack

ML-based System State Monitor - App SW Pack - Example

ML-Based System State Monitor App SW Pack - Example

ML-based System State Monitor - App SW Pack - Collaterals

ML-Based System State Monitor App SW Pack - Collaterals

ML-based System State Monitor - App SW Pack - SW Stack Block Diagram

ML-Based System State Monitor App SW Pack - SW Stack Block Diagram

Features

  • AI edge Computing
  • eIQ® machine learning (ML) software development and deep learning at the edge on i.MX RT Crossover MCUs
  • Complete and easy ML-based applications development, validation and performance analysis
  • Multiple inference engines usage: TensorFlow Lite Micro, DeepViewRT, Glow
  • Provides examples through an entire workflow of building and deploying on embedded targets with a real use-case
  • Related application spaces: system state monitoring, activity recognition, machine health (preventive maintenance, anomaly detection, failure identification)
  • Low-latency real-time system monitoring and failure identification
  • Applicable to time series real-time data
  • Can be used for other types of sensor data models that detect vibration

Supported Devices

  • i.MX-RT1170: i.MX RT1170 First GHz Crossover MCU with Arm® Cortex®-M7 and Cortex-M4 Cores
  • LPC55S6x: High Efficiency Arm® Cortex®-M33-Based Microcontroller Family
  • K66_180: Kinetis® K66-180 MHz, Dual High-Speed & Full-speed USBs, 2MB Flash Microcontrollers (MCUs) based on Arm® Cortex®-M4 Core

Downloads

1 download

  • Embedded Software

    Application Software Pack - ML State Monitor

Note: For better experience, software downloads are recommended on desktop.

Design Resources

Documentation

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1 documents

Hardware

3 hardware offerings

Related Software

5 software files

Note: For better experience, software downloads are recommended on desktop.

Training

1 trainings

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