2025 ASEE Annual Conference & Exposition

Python GUI for Data Acquisition

Presented at Instrumentation Methods and Techniques

Data acquisition (DAQ) involves sampling signals utilizing sensors that measure various electrical parameters, processing these signals, and displaying real-world results. This system is often implemented with a USB DAQ device (e.g., myDAQ, etc.) connected to a PC, or a controller module (e.g., Raspberry Pi Pico, Arduino, etc.), and software employed with graphical or text-based programming (e.g., LabVIEW, Matlab, etc.). With the increasing availability of free and open-source software package availability in Python and the increasing demand for Python skills among graduates, some courses are now incorporating Python for software development in practical applications. Python comes with a module called tkinter (short for “Tk interface”) that allows users to create simple and quick GUI programs. The tkinter module provides various graphical widgets (e.g., Button, Entry, Label, Radiobutton, etc.) with which the user can interact or view. A more robust method for creating advanced Python GUI program uses PySide6 and Qt Designer.

The goal of this paper is to utilize Python with the myDAQ to develop GUI programs suitable for lab projects in electrical and computer engineering and engineering technology, software engineering, and computer science programs. First, a lab project is shown to introduce students to Python GUI development using the tkinter module for simulating various waveforms (sinusoidal, square, and triangular), determining the spectrum of these signals, and displaying both the time-domain and frequency-domain representation of these waveforms. The GUI allows the user to select the waveform type, amplitude characteristics (peak amplitude, DC offset), frequency, signal duration, and sample rate. The second lab project introduces students to Python GUI development, using tkinter, for data collection with the myDAQ and plotting the time-domain and frequency-domain representation of the data collected. Then, these programs are developed using PySide6 and Qt Designer. Each project includes detailed engineering requirements, software code, and outcomes.

Authors

Prof. David R. Loker Pennsylvania State University, Behrend College [biography]

David R. Loker received the M.S.E.E. degree from Syracuse University in 1986. In 1984, he joined General Electric (GE) Company, AESD, as a design engineer. In 1988, he joined the faculty at Penn State Erie, The Behrend College. In 2007, he became the Chair of the Electrical and Computer Engineering Technology Program. His research interests include wireless sensor networks, data acquisition systems, and communications systems.
Prof. Teck Meng (Jonathan) Liaw Pennsylvania State University, Behrend College [biography]

Jonathan Liaw earned his B.Sc. in Applied Physics from the University of Portsmouth, UK, in 1983, followed by an M.Sc. in Computer Science from the University of Wyoming in 1985. He later obtained a second M.Sc. in Embedded Software from Gannon University in 2009. After serving as an adjunct professor at Gannon University, he joined Penn State Erie, The Behrend College, as a full-time faculty member in 2019. His research interests include machine learning, embedded systems design, and quantum computing.
Dr. Steven Nozaki http://orcid.org/0000-0003-4733-246X Pennsylvania State University, Behrend College [biography]

Ph.D. Engineering Education - The Ohio State University

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

« View session