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Research & Reviews: A Journal of Embedded System & Applications Review Article

VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion

  1. Sanket Khandu Sadgir Department. of Computer Engineering, MET Institute of Engineering, Nashik
  2. Aditya Sanjay Salve Department. of Computer Engineering, MET Institute of Engineering, Nashik
  3. Vaibhav Savliram Bodke Department. of Computer Engineering, MET Institute of Engineering, Nashik
  4. Sahil Jaimal Pathania Department. of Computer Engineering, MET Institute of Engineering, Nashik
  5. Ranjana P. Dahake Department. of Computer Engineering, MET Institute of Engineering, Nashik

Abstract

Road safety for bike riders remains a significant concern, with accident rates highlighting the need for advanced solutions to ensure rider protection and awareness. This paper presents “VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion”, a voice-activated, continuously operating assistance system designed to provide real-time, intelligent solutions for various riding scenarios. VERONICA integrates accident detection, low-traffic route navigation, traction control advisories, and weather updates into a single, user-friendly platform. By leveraging advanced voice recognition, natural language understanding (NLU) and Internet of Things (IoT) technologies, VERONICA delivers proactive guidance and timely alerts tailored to user needs. The system employs robust architecture, including microcontrollers, sensors, and APIs, to monitor and respond to environmental conditions. This paper explores the technical challenges, architecture, and implementation strategies involved in creating VERONICA, with a focus on ensuring reliability, responsiveness, and scalability for practical deployment in real-world scenarios. The results demonstrate that VERONICA significantly enhances rider safety and convenience, making it a transformative step forward in biking technology.

Keywords

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