Work

Source Code and Implementation Suite for: Development of an Artificial Intelligence-Based Vibration Monitoring System for Industrial Machines

Year: 2026

Type: dataset

Abstract: The following is the complete Arduino C++ firmware loaded onto the ESP32 DevKit V1 for realtime vibration monitoring and AI anomaly detection inference. It implements the 800 Hz data acquisition loop, DSP feature extraction, Int8 autoencoder inference, triple-check decision logic, dual-mode OLED display, and all four engineering reliability measures.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.23990276

Authors: Akindele, David Eniola, Daniyan, Ayomide, Daniyan, Ilesanmi, Phuluwa, Humbulani Simon

Institutions: Bells University of Technology, Afe Babalola University, University of South Africa

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W7225348046

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