Papers in Physics, vol. 10, art. 100004 (2018)

Received: 7 September 2017, Accepted: 1 March 2018
Edited by: A. Mart́ı, M. Monteiro
Reviewed by: E. Arribas, Universidad de Castilla La Mancha, Albacete, Spain
Licence: Creative Commons Attribution 4.0
DOI: http://dx.doi.org/10.4279/PIP.100004

www.papersinphysics.org

ISSN 1852-4249

Open-source sensors system for doing simple physics experiments

César Llamas,1 Jesús Vegas,1 Miguel Á. González,2 Manuel Á. González3∗

An open-source platform to be used in high school or university laboratories has been
developed. The platform permits the performance of dynamics experiments in a simple
and affordable way, combining measurements of different sensors in the platform. The
sensors are controlled by an Arduino microcontroller, which can be wirelessly accessed
with smartphones or tablets. The platform constitutes an economical sensing alternative
to commercial configurations and can easily be extended by including new sensors that
broaden the range of covered experiments.

I. Introduction

We have designed and constructed a low cost plat-
form that can be used to do simple physics ex-
periments combining different sensors’ data easily.
The purpose of this work consist in implementing
a cheap system that can be used in high schools
and universities regardless of their budget in di-
verse experiments, allowing a higher customization
than equivalent commercial sets.

II. System description

The initial requirements of the system are afford-
ability, simplicity, flexibility and extensibility. Un-
der the affordability requirement, we have decided
to employ systems that can be easily found on the
Internet at low prices. Simplicity means that users

∗E-mail: manuelgd@termo.uva.es

1 Departamento de Informática, Universidad de Val-
ladolid, 47011 Valladolid, Spain.

2 Departamento de F́ısica de la Materia Condensada, Uni-
versidad de Valladolid, 47011 Valladolid, Spain.

3 Departamento de F́ısica Aplicada, Universidad de Val-
ladolid, 47011 Valladolid, Spain.

with little to no training can easily use the sys-
tem in physics experiments without difficulty, but
also, that its construction does not require special
skills. Flexibility implies that the system should be
portable enough to work on different types of ex-
periments. Finally, its extensibility will allow users
to include additional sensors in the platform to en-
hance its capabilities and to use it in new experi-
ments.

In order to obtain an innovative platform as well
as to add sharing features to it, almost exclusively
open-source hardware and software components are
used. Within this approach, the physics teacher
community can work in open projects that can be
used by other teachers, thus reducing the work of
designing experiments with the platform. Follow-
ing this condition, the characteristics of the system
are published under a public GNU license in the
GitHub repository [1]. All the technical details of
the platform hardware and software are detailed
in that repository: software code, assembling dia-
grams and technical characteristics of the compo-
nents.

We initially decided to include sensors in the
platform that measure kinematic magnitudes: ac-
celerometer, gyroscope, distance sensor and light-
gate sensors. Other sensors, such as a magnetome-

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Papers in Physics, vol. 10, art. 100004 (2018) / C. Llamas et al.

Figure 1: A conceptual diagram showing the main com-
ponents of the system. It comprises a mobile unit that
includes several sensors (su, sv, ...) controlled by an Ar-
duino board and a portable unit with a Raspberry Pi
that communicates with the Arduino and establishes
a Wi-Fi network. It can also host additional sensors
(sx, sy, ...). The measurements of all the sensors can be
transferred into the users’ devices as series of vectors
M via a web front-end implemented in the Raspberry
Pi.

ter, a barometer, a thermometer, etc., can be easily
added later. Figure 1 shows a diagram of the use
of the platform in a physics experiment: the plat-
form includes a mobile unit, which can be attached
to a mobile body, containing sensors (su, sv,... in
the figure) and a portable unit responsible for the
Wi-Fi connection that allows the user to access the
measured data, but which can also include addi-
tional sensors (sx, sy,... in the figure). Measured
data are collected by the portable unit and orga-
nized in vectors (M = (ti, xi, ...)) in the figure)
also containing the time stamp of the measure-
ments. Whenever it is desirable and possible, the
mobile unit can be attached to a body in order to
study its movement. Then, the connection between
the mobile and the portable units must be based
on wireless communications, allowing the studied
body and the attached unit to move freely. In our
case, communications between the mobile and the
portable units are performed via Bluetooth.

The design of the mobile and the portable units
was based on previous works of embedded systems

[2] and they comprise the following elements:

• Mobile unit: An Arduino Nano v3 controls
a set of sensors. The version that has been
tested in laboratory experiments included an
infra-red line tracker, a motion processing unit
consisting of 3-axis accelerometer, gyroscope
and an ultrasound distance sensor. The AT-
MEL serial interface of the microcontroller is
connected to a HC-SR06 Bluetooth device. A
LiPo battery supplies power to all the system.
In its current design, the motion processing
unit can be replaced by a similar one that also
includes a 3-axis magnetometer together with
the accelerometer and gyroscope which would
permit to have a inertial measurement unit
with 9 degrees of freedom. This system is pro-
grammed in Arduino 1.6 [3] and it implements
a simple protocol through a serial wireless con-
nection, which is established by using Blue-
tooth connectivity that allows the initializa-
tion of the microcontroller as well as starting
and stopping data acquisition. The main speed
limitation in data measurements of the system
is due to the Bluetooth connection. Figure 2
(top) shows an implemented mobile unit used
in some physics experiments described below.

• Portable unit: It consists of a Raspberry Pi2
with Raspbian Jessie [4] as an operating sys-
tem. The core process of the unit is pro-
grammed in Go [5] and it governs the over-
all system as well as offering a web front-end.
This unit supports the Wi-Fi and bluetooth
connections. The data recorded in the mea-
surements are stored in a SD card, constituting
the local persistent storage unit. These data
can be accessed and retrieved by the users’
laptops or smartphones via Wi-Fi connection.
Additionaly, the portable unit can also allocate
other wired connected sensors using the GPI of
the Raspberry Pi. In the current configuration
of the system, four infrared emitter-receivers
are connected to it. These can be used, for
example, to measure instant speed at differ-
ent points along the trajectory of a body. The
unit can be powered by an ordinary USB bat-
tery, allowing to do physics experiments out-
side the laboratory. Figure 2 (bottom) shows
the portable unit.

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Papers in Physics, vol. 10, art. 100004 (2018) / C. Llamas et al.

Figure 2: Mobile (top) and portable (bottom) units of
the system. Portable unit shows the connections of four
additional infrared sensors attached to it (connections
A, B, C, and D in the figure).

III. Use in the laboratory

The system described above can be used in differ-
ent ways in the physics laboratory depending on
the users’ skill and knowledge of physics. We have
tested the platform in two basic experiments: an
air track in order to study an uniformly acceler-
ated movement and a pendulum to analyze periodic
motion and to obtain the gravity acceleration. Fig-
ure 3 shows the mobile and portable units being
used in the air track experiment. In this experi-
ment, the mobile unit included a 3-axis accelerom-
eter, a 3-axis gyroscope and an ultrasonic distance
sensor. In addition, four static infrared beacons
were placed at fixed points of the trajectory and
connected to the portable unit. The sampling fre-
quency was about 25 samples/s (∆t ≈ 0.0394 s).
This frequency was the result of a compromise be-
tween the measuring capabilities of the Arduino
and the data communication limitations between
the Arduino board and the Raspberry, using the
bluetooth connection. With the arrangement of
sensors used in the experiment, users can measure
the cart acceleration (accelerometer), average ve-
locities between different points (infrared beacons),
and the change in the position with time (ultra-
sound sensor and infrared beacons). From the data

Figure 3: Photography of an air track experiment us-
ing the platform. While the mobile unit is on the mov-
ing cart, the portable unit stays on the table with four
static infra-red beacons connected to it.

recorded by the different sensors, the user can an-
alyze the uniformly accelerated movement and the
relationships between kinematics magnitudes. On
the other hand, in a pendulum experiment, users
can combine the accelerometer and gyroscope mea-
surements to study the acceleration and speed in
different points and the periodic dependence of
both magnitudes. Infrared beacons can also be
used to measure the passage of time at different
points of the pendulum trajectory and enrich the
physical measurements. See [6] for more details on
an air track experiment.

Recorded data are stored in the SD card as a
plain CSV file with data of all the sensors used
in the experiment. The CSV files are transferred
to the users’ computer or mobile devices using the
Wi-Fi established by the portable unit. The rows of
the CSV file are tagged with the acquisition time,
in order to ease the analysis of the data by sim-
ply importing the file on any spreadsheet program.
Figure 4 shows some results of the measurements
with the air track. The measurements of the ultra-
sound distance sensor and the component of the ac-
celerometer along the direction of the movement are
represented as a function of time. From the data
shown there, it can be observed how the experimen-
tal noise of the ultrasound sensor increases notice-
ably with the distance to the reflecting screen. We
have checked this noise and, according to our exper-

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Papers in Physics, vol. 10, art. 100004 (2018) / C. Llamas et al.

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-2

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y=0.8 - (1/2)(0.2)(t-56.75)
2

average acceleration a=-0.2 m/s

D
is

ta
n
c
e
 (

m
)

A
c
c
e
le

ra
ti
o
n
 (

m
/s

2
)

t (s)

Distance
Acceleration az

Figure 4: Example of combined data recorded with the
platform in an air track experiment. The dependence
of the distance and the acceleration along with the di-
rection of movement recorded in the same experiment
are shown jointly.

iments, it is due to the air exiting from the air track
holes. Reducing or eliminating the airtrack pump-
ing, that noise drastically decreases, as well as when
the distance between the sensor and the reflecting
screen decreases. This can be seen as a possible
limitation of the used sensor, which can be solved
using, for example, an optical distance sensor. The
superposition of the data from the accelerometer
and distance sensors allows a clear identification of
the collision events between the cart and a rub-
ber band at the end of the air track. From the
diference in distances reached after consecutive re-
bounds (marked as example in the figure) users can
obtain the restitution coefficient of the collision.
Complementary, from the accelerometer data, users
can obtain the change in speed during each collision
and compare that result to the one obtained by
analizyng the maximum distance before and after
the bounce. As an illustrative result, a parabol-
lic curve y = 0.8 − (1/2)0.2(t − 56.75)2 is shown
in the figure. The distance 0.8 was chosen to dis-
place a little the theoretical curve upwards over the
experimental points for clarity. The acceleration -
0.2 m/s2 corresponds to the average acceleration
measured by the accelerometer sensor as shown in
the figure. The agreement between different sen-
sor data can help users to investigate relationships
between different magnitudes in an experiment.

IV. Discussion

A cheap open-source system to be used in simple
experiments has been developed. It comprises the
hardware and software of a sensorized platform.
The technical characteristics and the control soft-
ware of the system can be downloaded for free from
the Github repository [1]. The system permits the
measurement of different magnitudes in the same
experiment and the analysis of various phenomena.
The electronic components used in the system can
be acquired on the Internet by less than 100e, and
additional cheap sensors can be also included. Un-
like commercial sensor systems, this one constitutes
an extensible and customizable platform that can
be modified by adding other sensors and includ-
ing other software characteristics. The use of the
Githup repository also allows the collaboration be-
tween users that can add new characteristics to the
platform.

Acknowledgements - This work has been sup-
ported by University of Valladolid teaching innova-
tion program under grant PID2016 82.

[1] C Llamas, J Vegas, M Á González, M Á
González,
https://github.com/percomp/OSHIWASP,
last accessed September 4, 2017.

[2] C Llamas, M Á González, C Hernández, J Ve-
gas, Open source hardware based sensor plat-
form suitable for human gait identification,
Pervasive Mob. Comput. 38, 154 (2017).

[3] https://www.arduino.cc/en/Main/Software,
last accessed September 5, 2017.

[4] https://www.raspbian.org/, last accessed
September 5, 2017.

[5] https://golang.org/, last accessed September
5, 2017.

[6] M Á González, A Gómez, M Á González,
Smartphones in the air track, examples and
difficulties, (unpublished).

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