Source of this article and featured image is Arduino Blog. Description and key fact are generated by Codevision AI system.

This article discusses a new approach to enhancing bicycle safety through voice-activated turn signals. The project, developed by Manivannan, uses an AI-enabled smart helmet with Edge Impulse and Arduino technology. It aims to address the issue of misinterpreted hand signals by allowing cyclists to activate turn signals with voice commands. The system relies on a trained machine learning model that distinguishes between voice commands and background noise. This tutorial is worth reading because it provides a practical example of integrating AI and embedded systems for real-world applications. Readers will learn how to build a voice-activated turn signal system using Arduino and Edge Impulse.

Key facts

  • The project uses an AI-enabled smart helmet to improve bicycle safety by allowing voice-activated turn signals.
  • Manivannan developed the system using Edge Impulse and an Arduino Portenta H7 microcontroller.
  • The machine learning model was trained with audio samples of the words ‘left’ and ‘right’ along with background noise.
  • The hardware includes LED strips, a 5V battery pack, and a protective container for the Arduino.
  • The system enables cyclists to signal without removing their hands from the handlebars.
See article on Arduino Blog
TAGS: #Arduino  #Bicycle safety  #Cycling technology  #Edge Impulse  #machine learning  #Smart helmet  #Voice activation