

14th International Symposium on Particle Image Velocimetry – ISPIV 2021
August 1–5, 2021

SmartPIV - an app for flow visualization by
cross-correlation and optical flow using smartphones

Patrick Mäder1∗, Constanze Poll1, Jonas Hüther1, Sebastian Jeschke1, Henning
Otto2, Christian Cierpka2∗∗

1 Technische Universität Ilmenau, Data-intensive Systems and Visualization Group, Ilmenau, Germany
2 Technische Universität Ilmenau, Institute of Thermodynamics and Fluid Mechanics, Ilmenau, Germany

∗ patrick.maeder@tu-ilmenau.de, ∗∗ christian.cierpka@tu-ilmenau.de

In recent years smartphones considerably changed our communication and are used on a daily (or even
every minute) basis especially by students without any difficulties. Fluid flows also belong to our daily ex-
periences. However, the education of the basic principles of fluid mechanics is sometimes cumbersome due
to its non-linear nature. This problem may be tackled in practical sessions applying flow visualization tech-
niques in wind or water tunnels and directly learn from own observations. Nowadays, often optical methods
like particle imaging velocimetry (PIV) or particle tracking velocimetry (PTV) are used for these purposes.
A typical PIV/PTV setup consists of a (double)pulse laser, a scientific camera and a synchronization device.
The costs for this equipment can easily add up to more than 100,000 euros and the installations and set up
of the systems requires experiences and is complex. For these reasons Universities often only offer practical
courses for a small amount of students and the students may not be allowed to use and set up the systems by
their own as the equipment is also needed for scientific research. Due to the COVID-19 pandemic it is also
often not allowed to share equipment or even to work in larger groups during practical sessions.

However, modern smartphones offer a great selection of different sensors and are easy to set up, at least
for students. The high frame rates of several hundred Hz provided by modern smartphones also enable
their use for PIV. Cierpka et al. (2016) have shown that it is possible to use a smartphone with a cw-laser
for reliable velocity estimates in a plane. Käufer et al. (2021) extended the system to stereoscopic PIV
using two action cameras and a modulated cw-laser and Aguirre-Pablo et al. (2017) even used smartphones
with colored LEDs for a tomographic reconstruction of the velocity field in a water jet. All these attempts
were based on recorded videos that were later processed on a computer with conventional PIV software.
However, only recently a survey among engineering students showed, that there is a strong interest in a
mobile application (app) to perform PIV measurements (Minichiello et al., 2021). Therefore, the aim of the
current study was to provide an app that allows for a direct (on-line) evaluation of the data in order to enable
the students to directly see how the flow behavior changes when certain boundary conditions are varied and
to already estimate if the data processing with the current video/evaluation setting will be successful. The
app can also be used to determine the different effects of parameter changes for the PIV evaluation later at
home.

The app was developed within a student software project in close collaboration between students of en-
gineering and computer science. It is available for Android and iOS in the app stores and can be downloaded
and used free of charge (TU Ilmenau, 2021). Since the ability for on-line flow visualization was most cru-
cial concerning computer performance also optical flow algorithms were implemented as these request much
less resources. After choosing the processing parameters (cp. Fig. 1, right) the user can directly process the
images from the live preview (cp. Fig. 1, left insert), record videos or process already stored videos.

Images as well as videos can be stored for later export for lab reports. In addition to the images a text file
and a csv file containing the data and parameter settings will be created that can be used for later analysis for
example to test different mean estimators and outlier detection methods that will typically be taught in lab
courses. Since for the conversion of the particle image displacement to physical coordinates the knowledge
of the optical magnification is necessary a module that allows for a quick calibration using a square on a
white paper with known side length was also included. Since typical fields of view are in the range of 1–
20 cm the side length of the calibration target can be adopted to these values. The app can be intuitively
controlled by users that are familiar with the video or photo function of their smartphones as the menus are
designed very similar. A photograph of the application of SmartPIV for a test flow of a cylinder wake using
a low power cw-laser diode is shown in Fig. 1(left).


Figure 1: Experimental setup for a students exercise evaluation the flow past a cylinder. The setup includes
a cw-laser diode for illumination and the smartphone with the preview screen of the SmartPIV app (left).
Menu for the different evaluation methods optical flow or cross-correlation (right).

In the presentation the implementation on the smartphones and the accuracy will be discussed and a
typical lab setup will be demonstrated.

Acknowledgements
Financial support in the frame of the fellowships for ”Innovations for digital teaching” from the Thüringer
Ministerium für Wirtschaft, Wissenschaft und Digitale Gesellschaft are gratefully acknowledged. The au-
thors would also like to thank all the students, namely Julia Bruischütz, Teresa Bravo Roger, Jonas Stephan,
Jonas Hiese, Marcus Orban, Marcel John, Christian Engelhardt as well as Jörg König for the support in the
lab.

References
Aguirre-Pablo AA, Alarfaj MK, Li EQ, Hernández-Sánchez JF, and Thoroddsen ST (2017) Tomographic

particle image velocimetry using smartphones and colored shadows. Scientific Reports 7:3714

Cierpka C, Hain R, and Buchmann NA (2016) Flow visualization by mobile phone cameras. Experiments in
Fluids 57:108

Käufer T, König J, and Cierpka C (2021) Stereoscopic PIV measurements using low-cost action cameras.
Experiments in Fluids 62:57

Minichiello A, Armijo D, Mukherjee S, Caldwell L, Kulyukin V, Truscott T, Elliott J, and Bhouraskar A
(2021) Developing a mobile application-based particle image velocimetry tool for enhanced teaching and
learning in fluid mechanics: A design-based research approach. Computer Applications in Engineering
Education 29:517–537

TU Ilmenau (2021) SmartPIV. https://play.google.com/store/apps/details?id=de.tu_ilmenau.
secsy.smartpiv https://apps.apple.com/us/app/smartpiv/id1471308387

https://play.google.com/store/apps/details?id=de.tu_ilmenau.secsy.smartpiv
https://play.google.com/store/apps/details?id=de.tu_ilmenau.secsy.smartpiv
https://apps.apple.com/us/app/smartpiv/id1471308387