Diagnostic oscilloscope with artificial intelligence

Abstract

This paper describes the design and implementation of an oscilloscope that can recognise individual measurement signals, communication protocols, and buses based on machine learning (ML), a subset of artificial intelligence (AI) . The oscilloscope is compact and fully portable. The device is powered by a battery, making it energy self-sufficient. The oscilloscope data can be visualised with a smartphone using the Scoppy app. The Raspberry Pi Pico W microcontroller can be connected via Wi-Fi or USB. The processing of the measured signals is not done in real time, but from exported data using MATLAB . A graphical user interface (GUI) has been designed in MATLAB for data processing using ML .