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Engine knocking detection using Audio

Project Description:

This project implements a real‑time engine knocking detection system on a resource‑constrained embedded platform. On‑board microphones capture combustion noise, a compact ML model classifies “knock” events in‑situ, and summarized diagnostics are pushed securely to a cloud backend for visualization, alerts and analytics. By enabling predictive maintenance and continuous performance monitoring, it helps prevent engine damage and optimize operational uptime.

Project Photo:

Board with ML model and Cellular device to transmit data to the server.

Board with ML model and Cellular device to transmit data

Student Team Members

  • Shantanu Misra
  • Baliraja Nemade
  • Swastid Kasture

Course Faculty

  • Andreas Andreou

Project Mentors, Sponsors, and Partners

  • Andreas Andreou