Development of a Mobile Robot for Remote Monitoring for Multimedia and Data Acquisition

Abstract

This research is based on the development of a mobile robot for remote monitoring and data acquisition. The project aims at improving the problem found in the available data acquisition systems. The available systems are stationary systems that make use of data loggers to store the acquired data and they also require human personnel to move the system from one place to another while some systems require that the user pay for an internet connection for storing the acquired data on the Internet. To eliminate these problems there is a need for a robot with the ability to move from one place to another, a robotic arm for taking readings from specific points and a direct RF connection for data acquisition. The robot makes use of four wheels for movement, three servos to achieve three degrees of freedom with a Wi-Fi camera and DHT11 sensor for real-time data acquisition. Data acquired from the sensor is been transferred wirelessly to the OLED display on the remote controller by the HC-11 RF transceiver module. From the results obtained, the robot has an average speed of 0.14m/s when carrying a payload of 1Kg and the accuracy of the robotic is ±2º. The power consumed in the busy mode is quite remarkable with a difference of 650mW as compared to the idle mode. Therefore, the system developed in this work will therefore reduce the risk posed to field agents since it does not require a supervisor on the monitored site. Also by replacing an online server for data logging by a wireless remote control interface with display, the cost of implementing the system was reduced.

Full text

Black Sea Journal of Engineering and Science 3(3): 115-123 (2020)
doi: 10.34248/bsengineering.727198
BSJ Eng. Sci. / Amir MEHRNO and Mehmet Serhat ODABAS
115
Black Sea Journal of Engineering and Science
Open Access Journal
e-ISSN: 2619 – 8991
Review
Volume 3 - Issue 3: 115-123 / July 2020
DEVELOPMENT OF A MOBILE ROBOT FOR REMOTE
MONITORING FOR MULTIMEDIA AND DATA
ACQUISITION
James AGAJO1, Ajao Lukman ADEWALE1, Okhaifoh JOSEPH2, Alao Emmanuel
OLAMIDE1, Bolaji ABDULRAHMAN1
1Department of Computer Engineeering, Federal University of Technology, P.M.B 65, Minna, Nijerya
2Department of Electrical/Electronics, Federal University of Petroleum Effurun, P.M.B 1221 Delta State,
Nigeria
Received: April 26, 2020; Accepted: May 26, 2020; Published: July 01, 2020
Abstract
This research is based on the development of a mobile robot for remote monitoring and data acquisition. The project
aims at improving the problem found in the available data acquisition systems. The available systems are stationary
systems that make use of data loggers to store the acquired data and they also require human personnel to move the
system from one place to another while some systems require that the user pay for an internet connection for storing
the acquired data on the Internet. To eliminate these problems there is a need for a robot with the ability to move from
one place to another, a robotic arm for taking readings from specific points and a direct RF connection for data
acquisition. The robot makes use of four wheels for movement, three servos to achieve three degrees of freedom with a
Wi-Fi camera and DHT11 sensor for real-time data acquisition. Data acquired from the sensor is been transferred
wirelessly to the OLED display on the remote controller by the HC-11 RF transceiver module. From the results obtained,
the robot has an average speed of 0.14m/s when carrying a payload of 1Kg and the accuracy of the robotic is ±2º. The
power consumed in the busy mode is quite remarkable with a difference of 650mW as compared to the idle mode.
Therefore, the system developed in this work will therefore reduce the risk posed to field agents since it does not
require a supervisor on the monitored site. Also by replacing an online server for data logging by a wireless remote
control interface with display, the cost of implementing the system was reduced.
Keywords: Mobile robot, Multimedia, Data acquisition, Remote monitoring
*Corresponding author: Department of Computer Engineeering, Federal University of Technology, P.M.B 65, Minna, Nijerya
E mail: agajojul@gmail.com (J. AGAJO)
James AGAJO
https://orcid.org/0000-0001-5773-4249
Ajao Lukman ADEWALE
https://orcid.org/0000-0003-1255-752X
Okhaifoh JOSEPH
https://orcid.org/0000-0002-4558-7410
Alao Emmanuel OLAMIDE
https://orcid.org/0000-0002-8790-3338
Bolaji ABDULRAHMAN
https://orcid.org/0000-0002-3799-0912
Cite as: Agajo J, Adewale AL, Joseph O, Olamide AE, Abdulrahman B. 2020. Development of a mobile robot for remote monitoring for
multimedia and data acquisition. BSJ Eng Sci, 3(3): 115-123.
BSJournals

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1. Introduction
These days, technology plays a very significant role in our
day to day activities. For over half a century now,
robotics has being a staple of Advance Manufacturing.
Even though, underdeveloped and developing countries
are really lacking behind in the field of robotics
(Pooventhan et al., 2015), automated inventions that can
behave in a similar way to a human have been recognized
all through history. The majority of them were created
for entertainment purposes. Fiction writers have found
enormous success in writing about robots in diverse
situations which imply that the robot was part of
everyday conversation and imagination.
The term robot was first used in a Czech play called
Rossum’s Universal Robots (R.U.R), by Karl Capek in
1921. In the play a race of humanoid robots turned
against their masters and destroyed them, this is an idea
that is often always associated with robots. Still in today’s
technological age, the accurate definition of the word
robot is a subject of debate. Most definitions of robot are
rather broad and may possibly encompass any number of
recent devices from a dishwasher, a timer-controlled
compact disc play, an autonomous CCTV camera, to an
Unmanned Aerial Vehicle (UAV).
A more precise definition of robot was stated by the
Robot Institute of American that; “A robot is a
programmable multifunctional manipulator designed to
move materials, parts, tools or specialized devices
through variable programmed motions for the
performance of a variety of tasks”. George Devol and
Joseph Engelberger in 1956, created the world's first
robot company. By the 1960s, robots were employed in
the General Motors automobile plant in New Jersey for
carrying car parts around. Robots have substituted
humans in carrying out some task due to their sustained
development. They are even used at homes as toys,
vacuums cleaners, and as programmable pets, robots are
now components of many aspects of industry, science,
medicine, construction, space exploration, food
packaging and are even used to carry out
surgeries.(Pradnya et al., 2015)
Monitoring also called surveillance is the process of
watching, observing, keeping track of, listening to, or
checking (something) for a special purpose over a period
of time (Agajo et al., 2012). Hence, monitoring may be
applied to observations done from a distance by the use
of electronic equipment (like CCTV cameras), or by
intercepting electronically transmitted information (like
phone calls or Internet traffic). This could also refer to
relatively, simple no or low-technology methods such as
postal interception and human intelligence agents (Agajo
et al., 2012).
For this application, monitoring robots most have a
camera as an analogy to the human eye for watching the
monitored environment, sensors for measuring physical
phenomenon and limbs in the form of actuators for
reaching out to objects and for variable movements in
remote areas (Devjyoti et al., 2015). The use of cameras
mounted at a fixed point like the CCTV cameras is not
that useful as the view of the camera cannot be adjusted
in real time and obstructions like trees may block the
view of the robot (Sivasoundari et al., 2015).
Manned monitoring missions are critical to acquiring
useful intelligence, but sending human personnel into
sensitive areas can often be too dangerous and may
result in the loss of the precious life of field researchers.
Furthermore, the available data acquisition systems are
usually stationary systems with a data logger that
requires human personnel to change the position of the
system. The problem of such stationary monitoring
systems is that the data acquired is not real time, it is just
for a particular location since the system is immobile and
there is the possibility of loss or corruption of the
acquired data on the system by unforeseen
environmental disasters like earthquake, flood and heavy
wind storm or by the deliberate alteration of the
acquired data by a third party.
Although some standalone data acquisition systems do
exist, they always require that the systems connect to a
server and dump the acquired data in a database. The
problem with such system is that the user will have to
pay an internet service provider (ISP) for a connection to
the internet and in a developing country like ours such a
system cannot be relied on due to the poor network
experienced in remote areas. Furthermore, the user will
have to use a secured virtual private network to ensure
the confidentiality of the data acquired. That is why in
this research work a direct radio frequency
communication was employed between the user and the
monitoring robot.
2. System Methodology
2.1 System Overview
The mobile robot is a device with the ability to move
from one place to another through the use of rotating
wheels. The system is made of wheels, a camera, sensors
and robotic arm. The wheels will enable the robot to
move around during the monitoring operation. This
wheel is made of two tyres for forward and backward
movement and two front tyres for direction that is left
and right movement forming a system of four wheeled
vehicle with a good balance. The robot is being powered
by a 12V DC battery with considerable amperage rating
to operate the robot for a significant amount of time.
(Ahmed et al., 2016).
The robot’s wheels are controlled using a customized
handheld remote control that uses Radio Frequency (RF)
waves for communication. This enables the user to
effortlessly control the movement of the robot around
the monitored site. Robotic arm is used for picking
objects on the ground or moving obstacles, this function
is also controlled by the user. The camera installed on the
robot provides a real-time video stream of the
environment to the user while moving the robot around.

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All of these operations are coordinated by the Arduino
microcontroller. The overall system block diagram is
described in Figure 1.
Figure 1. Overall block diagram for the Mobile Robot
System for Data Acquisition.
2.2 The System Objectives
The key objective of the remote monitoring robot is to
enable use of robots in performing various tasks that are
very risky to human health. And the two obviously
dangerous tasks known to man are monitoring and data
acquisition especially in remote areas with harsh climatic
conditions. Additionally, the robot will be able to receive
instructions, and transmit the data it obtain in real time,
thereby improving the reliability of data obtained since
there is no middle man between the system and the
researcher (user).
2.3 System Flow Chart
The various operation phases of the monitoring robot
and it remote control interface is as shown in Figure 2.
Figure 2. Monitoring robot flow chart
2.4. System Hardware Design Considerations
The system hardware section comprises of the various
physical electronic and electromechanical components of
the system. The hardware section comprises of two
major subsystems: the robot body and the wireless
remote control.
2.5. Mobile Robot Unit
Basically, the robot body is the actual field agent that
moves around the monitored area, it receives
instructions on the direction to follow from the remote
control and also transmit the data it receives from the
environment to the remote control interface. It is made
up of the Power Supply Unit, Microcontroller Unit,
Movement Unit, Transmission Unit, Video Streaming
Unit, Sensor Unit and Robotic Arm Unit see schematic in
Figure 3.
Figure 3. Circuit Diagram of the Robot Body
2.6. Robot Power Supply Unit
A DC to DC converter circuit is implemented where the
11.1V from the lithium ion battery is passed through
LM7807 linear voltage regulator which helps to drop the
voltage to 7V for the servos and motors. A LM7805 linear
voltage regulator is also connected to the battery to
provide drop the constant 5V for the DHT11 sensor and
the motor driver. The DC port connected to the battery
can be used to charge it directly using a 12V DC power
adapter.
An AC Power Supply Source is discarded in order to
reduce the weight that will be added to the system
through the use of an AC transformer which requires a
smoothing stage and a voltage regulation and
stabilization stage. (Anand and Vikram,2016)
2.7. Movement Unit
This unit provides mobility to the robot and therefore
enables the robot to move from one place to another
while monitoring the site. It comprises of the motor
driver, two motors and four wheels. Two of the wheels
are connected to one of the geared motor at the back of
the robot for moving the robot forward and backward
while the other two wheels are connected to the motor at
the front for turning the robot to the left or right
direction. These movements are all achieved with the
help of the L293D motor driver being interfaced with the
microcontroller. The speed of the robot was calculated
using the following formula;
V = Eb + IaRa, V is the supplied voltage,
Eb is the back EMF, Ia is the armature current of the

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Motor in the robot, Ra is the armature resistance.
2.8. Arduino Microcontroller Unit
In the heart of the mobile robot is the Arduino Nano,
which is one of the many varieties of the Arduino
microcontroller series. Arduino Nano is a compact,
complete breadboard-friendly development board with
is based on the ATmega328. It has similar functionalities
to Arduino Uno since they make use of the same type of
Atmega chip in Figure 4.
Figure 4. The remote monitoring robot microcontroller
2.9. Transmission Unit
Wireless communication between the robot body and the
remote control is carried out by theHC11 RF transceiver
module. The HC11 transceiver makes use of the Universal
Asynchronous Receiver and Transmitter (UART)
protocol at a baud rate of 9600 bits per seconds. It
provides the medium for carrying the data from the
mobile robot to the remote control interface and vice
versa. The module was interfaced with the Arduino
microcontroller and mounted on the body of the robot
with the antenna pointing upwards (All on Robots, 2016).
2.10. Sensor Unit
The sensor unit is made up of the DHT11 sensor and Wi-
Fi camera. The Temperature and Humidity is acquired
using the DHT11 sensor because of it stability. The
sensor was interfaced with the microcontroller and the
microcontroller is programmed such that the readings
obtained from the sensor are transmitted wirelessly to
the remote control which displays the values in real time.
A live video stream of the environment being monitored
is captured and transmitted using the onboard Wi-Fi
camera. MD81 Wi-Fi camera was chosen because it
works in a hotspot mode such that it serves as a wireless
access point for the receiving device which could be a
mobile phone, laptop or any other digital electronic
device that support video streaming over Wi-Fi (Anand
and Vikram ., 2016)
2.11. Robotic Arm Unit
The robotic arm is made of three servos connected in
such a way that allow a rotational motion of the arm to
enable the robot to pick or manipulate objects in the area
being monitored. The linkage is as shown in Figure 5.
2.12. Wireless Remote Controller Unit
The wireless remote control is used to direct the robot
and to also receive the data transmitted by the robot.
When the robot is turned on it communicates with the
remote control by transmitting the readings from the
sensor to the remote control which in turn display the
readings. The remote is made up of the Power Supply
Unit, microcontroller Unit, push buttons Unit,
Transmission Unit and the Display Unit.
Figure 5. A robotic arm made of servo motors
Figure 6. Circuit Diagram of the Wireless Remote
Controller Unit
2.13. Interfacing Servo Mechanism with Arduino
Each of the servos require a pulse width modulated
(PWM) signal to work and so they were all connected to
PWM enabled pins of the Arduino. The first, second and
third servo were connected to pin 9, pin 10 and pin 11 of
the Arduino respectively. By so doing it becomes easy to
move the arm from one position to another.
2.14. Interfacing Geared DC Motors and Motor Driver
to Arduino
The geared DC motors were required for the robot to
move from one place to another. The major challenge
with interfacing these motors is that they cannot be
powered directly by the Arduino microcontroller. This is
because the Arduino can only supply a maximum voltage
of 5V and a current of 40mA but the motors require
minimum of 7V and 100mA current.
Therefore, to successful interface them together the
L293D motor driver was connected between the Arduino
board and the Geared motors. The Arduino pins 2, 3, 4
and 5 were connected to the L293D input pin 4, 3, 2 and
1 respectively. Then motor1 was connected to output pin

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1 and 2 of the motor driver while motor2 was connected
to output pin 3 and 4 of the motor driver. Vss pin of the
motor driver was connected to the battery supply voltage
and the ground pin was connected to the battery’s
ground pin. The overall system circuit diagram is shown
in Figure 7.
Figure 7. Monitoring Robot Overall System Circuit
Diagram
2.15. System Software Design Considerations
The various units of the remote monitoring robot require
a software program on the Arduino in order to
coordinate their various operations. And so the system
was first simulated before the actual implementation.
The major software used is Proteus ISIS and the Arduino
IDE. Proteus being a Virtual System Modeling and circuit
simulation application was used to design and simulate
the robot’s circuitry. Arduino IDE is specifically designed
for the Arduino microcontroller series, it makes it very
easy to write programs and upload to the board.
2.16. System Mathematical Model
This section describes the mathematical calculations that
were put into consideration during the selection of the
actuators used. The major components of the robot that
require mathematical consideration are the motors and
the servo mechanism used in constructing the robotic
arm. The motors and servos were selected base on the
result obtained as shown below.
2.17. Robotic Arm Inverse Kinematics
This is the process of calculating the joint angles, in order
to obtain a desired position. The angles and direction of
the end effector can be obtained from the following
mathematical equation.
From Figure 9, using cosine rule and Pythagoras theorem
we get;
 



 (1)
Since  (2)
Where  is the angle between the shoulder and elbow
servo motor,
 is the angle between the elbow servo and the end
effector,
 is the angle between the base and the shoulder servo
motor. Then equation (1) becomes
 



 (3)
  


 (4)
Hence,   


 
From the Figure 9,


 
  
 (7)
But      (8)
   
 (9)
   
 (10)
     (11)
Then  can be expressed as
   
   
 (12)
Therefore the required angle for the base servo motor,
second and third degree servo motor are 
respectively.
Figure 8. Robotic Arm Free Body Diagram.
2.18. Robot Arm Degree of Freedom
Robot arm degree of freedom is very important since the
robot will be used in place of a human hand for taking
measurements of specific points and for picking and
placing objects. That why the robot has four degree of
freedom. The four degree of freedom of the robot is as
shown in Figure 10.
First Degree: is the movement of the base of the robot

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120
which is equivalent to the movement of the human waist.
Second Degree: is the up and down movement of the
robot arm servo which is similar to the movement of a
human shoulder. Third Degree: is the forward and
backward movement of the robot arm as compared to the
human elbow. Fourth Degree: is the open and close
movement of the grippers similar to the movement of the
human fingers.
Figure 9. Robotics arm on X Y plane
Figure 10. Robot arm degree of freedom
2.19. Hardware Development on Vero Board
As stated earlier the system was first designed and
simulated using Proteus ISIS software. Although, the
simulation was successful, it is not enough to conclude on
the behavior of the system. To do this, the various part of
the system were first assembled and tested on a
breadboard before soldering on the Vero board. The
developed hardware is shown in Figure 11.
2.20. Performance Evaluation
The performance metrics used in this project is latency,
cost of implementation and power consumption. The
primary goal of presenting the latency of the video
stream transmitted from the camera, the overall power
consumption and cost of implementation is to help future
researchers to wisely select their components and
methodology.
2.21. Camera Latency
To calculate the latency of the video stream, the camera
was powered and the software used for displaying the
video stream was used to record the bits per seconds of
the transmission and the frame rate while varying the
robot position.
2.22. Power Consumption
As a remote monitoring robot the performance is greatly
influenced by the power consumed by the system since it
determine how long the system can perform it duty of
monitoring and data acquisition. The result obtained for
the system idle mode and busy was recorded. The idle
mode is a situation where the system is working like the
conventional stationary system while the busy mode is
the situation where the system is fully functional.
Known: Battery Voltage, V=7volt
power, P= 7*I(current) (13)
Figure 11. Robot connection on vero board
3. Testing Result
After designing and simulating the system using Proteus
ISIS simulation software the connections were then
tested on a breadboard to ensure the system behavior is
as expect before soldering the components onto the Vero
board. The final packaging of the robot body, the remote
control and the video stream from the camera is shown
in Figures 12, 13 and 14.
Figure 12. Robot body during testing

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Figure 13. Remote control during testing
Figure 14. Video stream from the camera during testing
Various tests were carried out on the system to ensure
the system was functioning as expected. The
microcontroller output pins were first tested by running
sample codes to ensure that the digital pins are able to
perform the desired input and output function.
3.1. Robot Speed
The speed of the robot was tested base on the amount of
weights that were added to the system in view of the fact
that the speed of the robot is inversely proportion to the
weight. Table 1 shows the result of adding a weight of
0.1-2Kg to the system. Robots speed test was carried out
over a distance of 10 meters, the time taken by the robot
was obtained using a stop watch and recorded as shown
in Table 1, Figure 15 also gives a graphical
representation of the data obtained and the resulting
speed was calculated using the speed equation in section
3.
3.2. Robot Arm Position
The degree of accuracy of the robotic arm is also very
important since it determines how correctly the system
can acquire data at strategic points. The higher the
accuracy the more reliable the data obtained. This is
because the system is expected to be able to change the
position of the arm as quickly as possible while taking
readings. The arm position was tested by writing
different pulse width modulation signals to the servo
from 0° through 180°. A mark was placed on the servo
arm which was used to observe and record the deviation
of the arm from the expected angle and then used to
recalibrate the servos. The results obtained are shown in
Table 2, 3 and 4.
Table 1. Robot speed test
Weight
(gram)
Distance
(m)
Time
(s)
Motor Speed
(m/s)
100
10
40
0.25
200
10
44
0.22
400
10
50
0.20
600
10
56
0.18
800
10
62
0.16
1000
10
70
0.14
1200
10
77
0.13
1400
10
83
0.12
1600
10
92
0.11
1800
10
103
0.10
2000
10
102
0.08
Table 2. Shoulder joint
Test
S/N
Expected
E (º)
Actual
Angle A
(º)
Deviation
D=A-E
(º)
Error
E=D/E
(%)
1
0
0
0
0
2
15
13
-2
-13.33
3
30
31
1
3.33
4
45
46
1
2.22
5
60
58
-2
-3.33
6
90
92
2
2.22
7
135
134
-1
-0.74
8
180
181
1
0.56
Table 3. Elbow joint
Test
S/N
Expected
E (º)
Actual
Angle A
(º)
Deviation
A-E (º)
Error
E=D/E
(%)
1
0
0
0
0
2
15
14
-1
-6.67
3
30
32
2
6.67
4
45
43
-2
-4.44
5
60
58
-2
-3.33
6
90
91
1
1.11
7
135
134
-1
-0.74
8
180
179
-1
-0.56
Table 4. Gripper
Test
S/N
Expected
E (º)
Actual
Angle
A (º)
Deviation
A-E (º)
Error
E=D/E
(%)
1
0
0
0
0
2
15
17
2
13.33
3
30
31
1
3.33
4
45
44
-1
-2.22
5
60
58
2
3.33
6
90
89
-1
-1.11
7
135
133
-2
-1.48
8
180
178
2
1.11

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Figure 15. Graph showing the speed with respect to
added weight
Figure 16. Graph showing the speed with respect to
added weight
3. 3. Performance Evaluation
The performance of the system was evaluated base on
the latency, cost of implementation and power
consumption.
3. 4. Camera Latency
Figure 4 presents the graphical view of the recorded
values for speed of the video stream obtained from the
camera at various distances from the robot.
Figure 17. Graph showing transmission rate with respect
to Distance
3.5. Power Consumption
Table 5 shows the result obtained when robotic system is
in the idle mode and busy mode after performing five (5)
different tests.
Table 5. Power consumption
Test
S/N
Idle Mode I (mA)
Power(mW)
Busy Mode I (mA)
Power(mW)
1
110
770
850
5950
2
103
721
770
5390
3
115
805
820
5740
4
108
756
830
5810
5
105
735
795
5565
Figure 18. Graph showing power consumed with respect
to the system mode
3.6. Discussion of Result
The result obtained in the robot speed test as shown in
Table 1, shows that the average speed of the robot as
regard to the weight of the payload is 0.14 meters per
second. This is equivalent to 900 meters per hour which
is very reasonable since the robot is not really expected
to move too fast while taking readings. Figure 15 shows
that the speed of the robot decreases with the weight.
From Table 2, 3 and 4 it can be clearly observed that
there were deviations of each of the servo arm from the
expected position. The three servos have an average
error of ± 2° or ±13.33%, but by calibrating the servos
from the programming code, the error was reduced to
±1°. By so doing the accuracy of the robotic arm position
was improved for acquiring data at a specific position.
The transmission rate of the camera is 200Kbps at about
60 meters from the camera as shown in Figure 14. At this
transmission rate the video stream is quite commendable
with 15 frames per second. Though, the transmission
rate of the camera can be improved by using a wireless
repeater to reproduce the signal and boost the range of
the transmission.
The power consumed by the system in the idle mode is
very low as compared to the power consumed in the busy
mode which is as expected because in the idle mode the
robotic wheels and the servos were not in use and they
both consume a lot of current. The wheels consume an
average of 100mA each making a total of 200mA for the
two motors, while the servo motors used consumes an
average of 150mA each making a total value of 450mA.
So there is an average difference of 650mA current
consumption as shown in Figure 18.

Black Sea Journal of Engineering and Science
BSJ Eng. Sci. / Amir MEHRNO and Mehmet Serhat ODABAS
123
5. CONCLUSION
It apparent that monitoring and data acquisition are very
important factors in our day to day activities. Therefore,
the mobile robot for remote monitoring and data
acquisition developed in this project will help to improve
the availability and reliability of quality data and most
importantly, it will help to reduce the risk to the life of
field agents or researchers.
Therefore the aim of this project which is to develop a
mobile robot for remote monitoring and data acquisition
has been achieved. And from the result obtained it can be
concluded that the system is efficient, reliable and cos1t
effective.
5.1. Recommendations and Future Works
The following are recommended for future works on the
design of a mobile robot for remote monitoring and data
acquisition;
 The range of the video stream transmitted can be
increased by connecting the camera to the
internet which implies that the video can be
accessed anywhere in the world.
 The robot wheel could be upgraded to more
powerful wheels to improve the mobility and
tolerance of the system in rough terrains.
 Servos with more power and torque can be used
in order to increase the maximum load that can be
lifted by the robotic arm.
Conflict of interest
The authors declare that there is no conflict of interest.
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