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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