An Intelligent Robotic Platform for Conducting Geodetic and Ecological

Surveys of Water Bodies

Andrii Tkachuk

1 a

, Mariia Hrynevych

1 b

, Tetiana A. Vakaliuk

1,2,3 c

, Oksana A. Chernysh

1 d

and Mykhailo G. Medvediev

4 e

Zhytomyr Polytechnic State University, 103 Chudnivsyka Str., Zhytomyr, 10005, Ukraine

Institute for Digitalisation of Education of the NAES of Ukraine, 9 M. Berlynskoho Str., Kyiv, 04060, Ukraine

Kryvyi Rih State Pedagogical University, 54 Gagarin Ave., Kryvyi Rih, 50086, Ukraine

ADA University, School of Information Technologies and Engineering, Baku, AZ1008, Azerbaijan

Keywords:

Robotics, Geodesy, Measurement, Acidity, Temperature.

Abstract:

The article considers the relevance of using a new intelligent robotic platform to quickly conduct basic re-

search on water quality assessment in reservoirs and analyze the relief of the reservoir bottom, preserving all

the data. The paper proves that using an intelligent platform for water analysis signiﬁcantly facilitates the

research. Moreover, it increases the studied area of the reservoir. It simpliﬁes the process of establishing the

correspondence of data to a particular place on the reservoir compared to classical methods of water quality

analysis in the reservoir. It describes the platform’s advanced design, which consists of a housing, a control

board, sensors, actuators such as servo motors and a brushless motor, a radio module, a GPS module, and a

motor speed controller. In addition, it illustrates the cutting-edge platform control panel. The article analyzes

a functional diagram of an intelligent robotic platform for water quality assessment and bottom topography. It

presents the study of the developed system carried out on the reservoir, the main idea of which was to study the

correctness of the system’s operation, evaluate the effectiveness of the conducted studies, and display water

quality sensors. The paper studies an ultrasonic sensor for measuring depth and sensors for water acidity and

temperature. It presents the outcomes of the developed monitoring system experiments that resulted in a map

of the reservoir’s bottom area and certain conclusions on water quality.

1 INTRODUCTION

Modern realities signify a rapid increase in consump-

tion and the amount of waste. Therefore the ques-

tion arises whether new digital technologies can com-

pensate for these changes. The answer is obvious: it

is necessary to look for new solutions that will help

solve the problem of climate change and contribute to

preserving the well-being of the entire planet.

Water pollution is the negative change in the phys-

ical, chemical, and bacteriological water properties

caused by an excess of inorganic substances (solid,

liquid, gaseous), organic, radioactive, or heat, which

limit or prevent the use of water resources for drink-

https://orcid.org/0000-0003-2466-6299

https://orcid.org/0000-0001-9183-5211

https://orcid.org/0000-0001-6825-4697

https://orcid.org/0000-0002-2010-200X

https://orcid.org/0000-0002-3884-1118

ing and economic purposes.

Natural reservoirs, such as oceans, rivers, and

lakes, can self-purify. However, getting too many pol-

lutants into their system can cause irreversible dam-

age. Therefore, it all depends on the number of pollu-

tants.

Too many chemicals, bacteria, and other microor-

ganisms cause severe water pollution. Chemical, or-

ganic, and mineral substances form colloidal solu-

tions and suspensions. Natural factors determine the

chemical composition of pollutants, for example, the

decomposition of substances in soil and rocks, the de-

velopment and death of aquatic organisms, and an-

thropogenic factors.

Consequently, a robotic platform enables remote

analysis of water in the reservoir to measure the acid-

ity of water, its temperature, and the depth of the

reservoir. In case of acidity increase and water pollu-

tion detection, it will be possible to take a water sam-

ple from a particular reservoir area and carry out a de-

Tkachuk, A., Hrynevych, M., Vakaliuk, T., Chernysh, O. and Medvediev, M.

An Intelligent Robotic Platform for Conducting Geodetic and Ecological Surveys of Water Bodies.

DOI: 10.5220/0012009600003561

In Proceedings of the 5th Workshop for Young Scientists in Computer Science and Software Engineering (CSSE@SW 2022), pages 50-56

ISBN: 978-989-758-653-8; ISSN: 2975-9471

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

tailed water analysis in the ground laboratory. More-

over, the ﬂoating platform takes real-time readings

from sensors and follows the executive mechanisms.

Thus, it detects the source of pollution and marks the

exact location by dropping a beacon in the highest

pollution concentration for further investigation of the

nature and pollution level.

Furthermore, the platform is a helpful tool for

training qualiﬁed economists and promoting the de-

velopment of environmental consciousness and mo-

tivation for transforming knowledge in behavioral

models.

2 THEORETICAL BACKGROUND

The problem of water pollution is becoming more

signiﬁcant. Some “mobile” laboratories allow con-

ducting research in ﬁeld conditions. However, it is

a long-term process that requires detailed preparation

and preliminary water sampling.

There are no absolute analogs of the system pre-

sented.

The automated surface platforms that are fully au-

tonomous or controlled are reviewed in (Dimitropou-

los, 2019; Brans, 2021; Rivero, 2022; Niiler, 2020;

agan, 2021). Therefore, they are suitable for ex-

treme conditions to research in the ocean or transport

cargo along a speciﬁc, established route.

Sea Machines (Sea Machines, 2023) highlight an

autonomous self-piloting system, which allows re-

mote control of the vessel, receives information from

sensors on the user interface, and has a complete pic-

ture of the vessel’s state.

Li et al. (Li et al., 2020) suggested a spectral pro-

cessing method for analyzing the reﬂectivity of water

samples and applied machine learning methods to es-

timate water quality parameters.

Therefore, the investigation aims to develop an in-

telligent robotic platform for conducting geodetic and

environmental research, which will be easy to man-

age, “mobile”, and fast compared to similar systems.

Moreover, it will also allow us to quickly make sets

of water samples for more accurate and detailed anal-

ysis in the laboratory. In addition, it contributes to

an actual experiment to assess the robotic platform’s

effectiveness and the system’s correctness.

Koval’ (Koval’, 2015), Bezvesilna et al.

(Bezvesilna et al., 2017) describe modern sensors

for measuring acceleration and gravity anomalies.

However, they do not indicate the feasibility of using

them in the design of intelligent robotic platforms.

Various ways to control intelligent robotic plat-

forms are suggested in (Chung et al., 2018; Tedeschi

and Carbone, 2014). An example of a fuzzy neural

network and a Kalman ﬁlter to control a mobile robot

is provided. A stabilization algorithm with the ap-

plied close-loop control system, including an inertial

measuring unit as a feedback sensor, is delivered. A

Control system is applied to calculate the engine an-

gles to achieve stability on the inclined surface.

3 RESULTS

3.1 The Structure of the Intelligent

Robotic Platform

Zhytomyr Polytechnic State University scholars have

developed an intelligent robotic platform for geodetic

and environmental research. According to the criteria

of “cost-effectiveness” and mobility, the new system

will be the best among its known analogs. The design

of the robotic platform (ﬁgure 1) consists of the fol-

lowing main elements: body; control unit (1), which

includes a microcontroller based on an Arduino Nano

board (2), a radio module (3), a JSN-SR04T-2.0 sen-

sor control board (4), a PH-4502C module to which

a water acidity sensor is connected (5); collectorless

engine (6), its cooling jacket (7), engine regulator (9)

connecting clutch (24) for transferring rotation from

the engine shaft to the deadwood shaft (23), which in

turn is connected to the propeller (22) ); the system is

and (13) are used as cargo compartment drives (25)

and (26), steering wheel drive (21) and water intake

mechanism drive; sensors for temperature (14), acid-

ity level (15), ultrasonic for measuring the distance

from the bottom of the platform to the bottom of the

reservoir (16), distance sensor (27); navigation of the

platform is provided by the GPS module (28) and the

antenna (29); overall emitters (17) – (20) help in driv-

ing in the dark.

The platform equipment is powered by a Turnigy

Li-Po 7.4V 5300mAh 2S2P 25C battery, which al-

lows you to use the robotic intelligent platform for

a long time and provides the necessary power supply

voltage for the correct operation of the system. An

Arduino Nano board built on an ATmega328 micro-

controller was chosen as the control device. It is com-

pact and enables all the tasks set in this project. For

remote data transmission and platform control, the

NRF 24L01P+ radio module is used, ensuring good

signal reception and transmission quality at a distance

of up to 1 kilometer. Furthermore, the following sen-

sors receive data about the environment: ultrasonic

distance sensor JSN-SR04T-2.0, which provides mea-

An Intelligent Robotic Platform for Conducting Geodetic and Ecological Surveys of Water Bodies

Figure 1: Structural elements of the robotic intelligent platform (a) the robotic platform (b).

surement of the distance from the swimming plat-

form to the bottom of the reservoir and thereby al-

lows displaying a map of the topography of the bot-

tom by constructing a graph based on the data re-

ceived from the sensor, as well as measuring depth

in a speciﬁc place of the reservoir and make a pre-

liminary calculation of the water volume of the reser-

voir; the DFRobot ADC151 water acidity sensor is

used to analyse water quality, which helps to explore

and determine the acidity of water almost instantly;

to measure the water temperature, a DS18B20 digi-

tal sensor is used with the function of an alarm sig-

nal for monitoring the temperature and the range of

the measured temperature from 55 to +125 °C; the

Sharp GP2Y0A21YK0F infrared distance sensor was

used to determine ﬂoating obstacles that may appear

in the path of the platform; to determine the exact lo-

cation of this system and further build a map of the

bottom and link the received data to exact coordi-

nates, the GPS module GPS NEO-6M SMA + IPEX

and the active antenna ANT GPS BY-GPS-07 SMA-

M were used to increase sensitivity and increase the

ratio “signal-to-noise” and reducing the impact of in-

terference. The executive mechanisms are in the form

of MG995 Tower Pro and MG996R-180 servomotors,

which are necessary to implement the water collection

mechanism for its further in-depth analysis, as well as

to ensure the movement of the swimming platform in

the required direction and to unload the cargo placed

in two cargo compartments on top of the platform.

3.2 Control Panel

We developed the control panel for the platform by

modernizing the existing panel, the structural diagram

of which you can see below.

Control is carried out by the Arduino Nano board,

which provides data processing. Moreover, it per-

forms the control device function and ensures data

processing from the GPS module and their recording

CSSE@SW 2022 - 5th Workshop for Young Scientists in Computer Science Software Engineering

Figure 2: Structural diagram of the remote control panel.

on a ﬂash drive.

Sticks are employed to control the platform re-

motely; buttons are used to drive the cargo compart-

ments and activate the water sampling system. LEDs

are used to display the status of the system.

The control panel receives and transmits data via

the NRF 24L01+ radio module. The received sensor

data from the radio module are processed by the con-

trol board and displayed on the OLED display of the

control panel.

3.3 Algorithms of System Operation

For the operation of the robotic intelligent platform, it

is necessary to organize the synchronous operation of

the swimming platform and the remote control (data

reception and transmission). First, according to the

system’s algorithm (ﬁgure 3), the controller ports are

conﬁgured, and the input data is zeroed. In this case,

the transmitter considers the robotic intelligent plat-

form, i.e., the initiator of the data exchange. Then

a request is sent to the air to connect to the control

panel. If there is no response, a cyclical request to

connect to the control panel is sent again. If there is a

connection and a signal is received, a response occurs

to work on exchanging data with the remote control

and checking the necessity of continuing work. If the

work is ﬁnished, the cycle ends. If the system contin-

ues, cyclical work with the remote control takes place

until the work with the remote control is ﬁnished.

The control panel operations algorithm (ﬁgure 4)

begins with initialization. Then, the remote control

acts as a receiver. Therefore, there is a wait for a free

request on the air to connect to the robotic intelligent

platform. In the absence of active requests, there is

a cyclic wait for a connection request. In the case of

Figure 3: The basic algorithm of the robotic intelligent plat-

form.

a connection and receiving a signal, it is essential to

exchange data with the platform and check the need

to continue work. If the work is ﬁnished, the cycle

ends.

3.4 Features of the System

When activating the data recording system for build-

ing a three-dimensional model of the reservoir bot-

tom, the system activation is checked, the GPS mod-

ule and the SD module are launched, and their set-

tings for operation are performed. The GPS module

needs time to connect to satellites and determine its

coordinates. Therefore, determining the coordinates

of the robotic platform location takes time. Then a

ﬁle is created to make further recordings of the depth

sensor data and the corresponding coordinates. In ad-

dition, a timer is started, which is set to 10 minutes

by default. During this time, the data will be recorded

in the created ﬁle. Next, the coordinates and depth

are cyclically read. Finally, this data is written to a

ﬁle with an interval of 30 seconds during the time set

by the timer. This data ﬁle is the basis for construct-

An Intelligent Robotic Platform for Conducting Geodetic and Ecological Surveys of Water Bodies

Figure 4: The basic algorithms of the control panel.

ing a wavelet diagram of the reservoir bottom section.

If the data recording system is activated again, it is

checked whether the coordinates of the module are

determined, and the work continues in the cycle. Oth-

erwise, the reactivation of the system is expected.

With the help of radio modules, such data as con-

trol signals from the remote control are transmitted.

They are responsible for the movement of the plat-

form, turning on/off the dimensions, and collecting a

water sample for deeper analysis. In addition, there

is a data transfer received from sensors, namely water

acidity level, temperature, depth, coordinates of the

platform location, and battery charge level.

To create a map of the bottom relief, ﬁrst of all, it

is necessary to collect data on the depth of the reser-

voir using an ultrasonic distance sensor JSN-SR04T-

2.0. Then, two more parameters are needed to build

a three-dimensional model. One of them is time, and

the other is coordinates, the determination of which

is performed using GPS data of the mobile platform

location on the reservoir. Finally, when conducting

research, it is necessary to choose a site on the reser-

voir and, moving through the reservoir step by step,

receive data from the depth sensor and coordinates

at these points, respectively, and write this data to a

ﬁle on the platform of the RPi 3B+ mini computer in-

stalled on the mobile platform.

3.5 Data Processing

The MATLAB system was used to process the data

and build a three-dimensional relief model of the bot-

tom of the reservoir, namely the Wavelet Toolbox,

which provides functions and applications for analyz-

ing and synthesizing signals and images. The tool-

box includes algorithms for continuous wavelet anal-

ysis, wavelet coherence, synchrosqueezing, and data-

adaptive time-frequency analysis. Using continuous

wavelet analysis, it is possible to study how spectral

functions evolve with time, identify common time-

varying patterns in two signals, and perform time-

localized ﬁltering. Discrete wavelet analysis helps to

analyze signals and images in different extensions to

detect discontinuities and other defects that are not

easily visible in the raw data. In addition, it is possi-

ble to compare signal statistics on multiple scales and

perform a fractal analysis of the data to reveal hid-

den patterns. Finally, with the Wavelet Toolbox, you

can obtain a sparse representation of data valid for de-

noising or compressing data while preserving impor-

tant features. Many toolbox functions support C/C++

code generation.

Figure 5: Recorded data from a ﬂash drive.

The investigation results prove that using wavelet

transformations at the given stage of work is not en-

tirely appropriate. Undoubtedly, it is necessary to

follow a clear route to use wavelet transformations.

For instance, it is crucial to select the coordinates of

CSSE@SW 2022 - 5th Workshop for Young Scientists in Computer Science Software Engineering

Figure 6: Intelligent robotic platform movement route and two-dimensional depth plot.

Figure 7: Three-dimensional model of the bottom of the

reservoir.

a speciﬁc section, which are autonomously traversed

robotically by the platform at the same speed, the

same passes, and exclude measurement errors due to

the inﬂuence of external factors.

4 CONDUCTING AN

EXPERIMENT

Before the experiment, the platform and all elements’

efﬁciency were thoroughly checked. Then, a shallow

Figure 8: Changes in water acidity in the reservoir.

Figure 9: Water temperature changes in the reservoir.

water body was chosen for the test launch of the in-

telligent robotic platform and the necessary data col-

lection. Finally, a route with different trajectories was

traversed, and sensor data were recorded, which was

the primary aim of the research.

All the research data is recorded in a ﬁle stored on

a ﬂash drive. It is convenient for further processing

An Intelligent Robotic Platform for Conducting Geodetic and Ecological Surveys of Water Bodies

and analysis. Some recorded data is shown in ﬁgure 5.

The GPS module determines the current location

and indicates the exact time regarding the location in

speciﬁc coordinates. The data analysis makes it possi-

ble to build a map of the intelligent robotic platform’s

route and a two-dimensional depth graph (ﬁgure 6).

Furthermore, a three-dimensional model of the

reservoir bottom was built based on the platform’s

route data and measured data at speciﬁc points along

the route. However, it is not highly detailed, as it con-

siders only the speciﬁed points of the route. Thus, to

increase its informativity, all intermediate points must

be ﬁlled with relevant data (ﬁgure 7).

According to the readings of the temperature and

acidity sensor at each determined point of the robotic

platform route, graphs of changes in these values were

built (ﬁgure 8, 9).

5 CONCLUSIONS

The research introduces a new intelligent robotic plat-

form for geodetic and ecological studies of water bod-

ies. It helps assess water quality and measure a wa-

ter body’s depth. It provides a detailed layout of all

structural elements, describes the methodology, and

clariﬁes further data processing. Sensitive system ele-

ments such as temperature, water acidity, and distance

sensor were chosen, which meet all platform instal-

lation requirements. Finally, it investigates the effec-

tiveness and correctness of the system performance on

a natural reservoir (a river and a lake). Furthermore,

all necessary measurements were taken, including a

water sample. Based on the results, conclusions were

made about the water quality in the reservoir. More-

over, three-dimensional models of the studied bottom

area and graphs of changes in the values (tempera-

ture and acidity) were constructed. In addition, the

research highlights the problem of using a wavelet di-

agram to describe the area of the reservoir bottom.

The installation has a set of functions, which can

be increased in the future, for example, adding the

function of work autonomy at speciﬁed points, which

contributes to building a full-ﬂedged detailed map of

the reservoir bottom. In addition, the article considers

the possibility of a more detailed analysis of water

locally.

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CSSE@SW 2022 - 5th Workshop for Young Scientists in Computer Science Software Engineering