Design and test of a low-cost turbidity
meter using an LED
A. Louise Ferris; Thomas Aumer; Theodore A. Corcovilos
Department of Physics, Duquesne University
efficient way of testing the turbidity(cloudiness) of a
water sample. Using an Adafruit Metro Mini board, a
color sensor, an LCD screen, and a red LED, we built
a device which measured the cloudiness of a sample
by measuring the amount of light emitted
perpendicular to a monochromatic light source by
the process of Mie Scattering. Once the device was
properly built, we used milk as a test sample, as the
turbidity of milk has been well studied and is less
toxic than the standard, formalin
The amount of light scattered by
the sample was measured by the
color sensor, allowing for turbidity
to be measured. Cloudier samples,
with higher concentrations of milk,
have a higher turbidity, measured
Figure 1. The completed device
in NTU (Nephelometric Turbidity
Units). Our device has a much
lower cost (about $50) than comparable commercial
units (about $1000).
Turbidity is the measure of a liquids cloudiness.
Turbidity is an important test of water purity because it
describes the amount of insoluble matter, such as silt,
algae or insoluble minerals such a iron rust suspended in
the water. Our goal in measuring turbidity is to test
drinking water and well water for contaminants (Ref. 3).
Turbidity is typically quantified in terms of
Nephelometric Turbidity Units (NTU), an empirical
comparison standard based on the amount of scattered
light from various concentrations of a
particular polymer (formalin) suspended in
water (Ref. 2). Because formalin is toxic, for
safety we instead use another wellcharacterized system as our comparison
standard: pasteurized homogenized whole
Figure 2. A cloudy
cow's milk (Figure 3, Ref. 4).
sample(50% milk) vs. a
clear sample(0% milk)
Optically, milk can be described as spheres of fat
suspended in water. The size of the fat globules in
homogenized milk have a median diameter of 0.46 m
and have a log-normal size distribution (Fig. 4, Ref. 6).
Turbidity is caused by the optical process of Mie
scattering (Ref. 1), which predicts the direction and
intensity of light as it is scattered off of particles of
similar size to the wavelength of the light.
Using the known distribution
of globules sizes we did a
Monte Carlo simulation
to predict the light intensity
scattered in each direction
(Fig. 5). Our device measures
the output at an angle of 90.
Figure 4. Globule size distribution
of homogenized milk. Data from Ref.
Figure 5. Simulation of red light scattering
from a milk fat globule. (Top) Scattering
efficiency as a function of exit angle. (Bottom)
Depiction of the same data with the length of
each outgoing arrow proportional to the light
intensity in that direction. (Calculated using
S Metro Mini board, an Adafruit
We used an Adafruit
AS7262 6-Channel Visible Light / Color Sensor, an
LCD screen, a red LED (650 nm output), and a 3-D
printed base to construct the device. We expanded
the capability of the sensor to turbidity in addition to
its previous use as a 6-color colorimeter. A cuvette
filled with a fluid sample is inserted in the middle of
the device, where the LED then flashes, allowing for
the color sensor to measure the amount of light that
was emitted through the sample. We started with
whole milk purchased from a convenience store and
bottled drinking water. From there, we diluted the
sample down for ranges from 100% milk to 0.01%
(see figure 8).
We designed a deviceTION
to establish a more cost
Figure 3. Turbidity of diluted whole milk (Data from
that more light is scattered up to some maximal
point. Beyond this the majority of light is absorbed.
The fitting equation used is an adaption of the BeerLambert law to include both scattering and
(NTU<650), a linear Taylor series approximation
using the same fitting constants works well.
Figure 8. Graph of all data, including equation of the fit, which was
derived from the Beer-Lambert law, along with the found parameters,
and the Taylor approximation, which uses the same parameters and
works for NTU<650. The triangle indicates outlier points not included
in the fit.
The first of our future goals are to update the
sensor and LED used to infrared light, in order to
reduce the absorption percentage. Additionally, we
aim to change to using a circular sample cell for user
convenience, and finally we aim to build a flowthrough submersible version of the device which can
be used in rivers and lakes for real time sensing.
1. Horvath, H. (2009). Gustav Mie and the scattering and absorption of light
by particles: Historic developments and basics. Journal of Quantitative
Spectroscopy and Radiative Transfer, 110(11), 787-799.
2. Kitchener, B. G., Wainwright, J., & Parsons, A. J. (2017). A review of the
principles of turbidity measurement. Progress in Physical Geography:
Earth and Environment, 41(5), 620-642. doi:10.1177/0309133317726540
3. National primary drinking water regulations. (2016). Washington, D.C.:
United States Environmental Protection Agency, Office of Ground Water
and Drinking Water.
4. S. Prahl "miepython library" https://github.com/scottprahl/miepython
5. Showcase Diagram of different Media [Chart]. (n.d.). In Relative Turbidity
Meter ITM-2. Retrieved from
6. Stocker, Sabrina, et al. Broadband Optical Properties of Milk. Applied
Spectroscopy, vol. 71, no.
5, May 2017, pp. 95162.
Figure 6. A cartoon rendition of the path of
As the concentration
of milk increases, we can see
Figure 7. The arrows show the
direction of the light, from the source,
through the water, and into the sensor
Funding for this project
and support for this project
was provided by the Duquesne Physics Department
and the Bayer School Scholars fellowship.
Summer Undergraduate Research Symposium 2019
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