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Home Robotic Security Bot Using TinyML For Robotics and XR Course - University of Eastern Finland

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This project demonstrates the use of TinyML for a home robotic security bot that can recognize footsteps and glass breaking noises. The system uses an Edge Impulse model to classify these sounds and takes appropriate actions such as lighting LEDs and triggering a buzzer.

Introduction

This project uses the TinyML Kit to build a home security bot capable of detecting specific sounds, such as footsteps and glass breaking. It leverages the Edge Impulse platform for model training and inference. Also included Obstacle Avoidance Code.

Hardware Requirements for ML features

  • TinyML Kit
  • LEDs (Red, Blue, Green)
  • Buzzer
  • Microphone

Software Requirements

  • Arduino IDE
  • Edge Impulse SDK
  • PDM Library

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