=Paper=
{{Paper
|id=Vol-3179/Paper_23.pdf
|storemode=property
|title=Control System of Electrotechnical Phytotron Complex with the Use of Internet of Things Technology
|pdfUrl=https://ceur-ws.org/Vol-3179/Paper_23.pdf
|volume=Vol-3179
|authors=Taras Lendiel,Nikolay Kiktev,Natalia Pasichnyk
|dblpUrl=https://dblp.org/rec/conf/iti2/LendielKP21
}}
==Control System of Electrotechnical Phytotron Complex with the Use of Internet of Things Technology==
https://ceur-ws.org/Vol-3179/Paper_23.pdf
Control System of Electrotechnical Phytotron Complex with the
Use of Internet of Things Technology
Taras Lendiel a, Nikolay Kiktev a, b and Natalia Pasichnyk a
a
National University of Life and Environmental Sciences of Ukraine, Heroiv Oborony str., 15, Kyiv, 03041,
Ukraine
b
Taras Shevchenko National Univercity of Kyiv, Volodymyrs’ka str., 64/13, Kyiv, 01601, Ukraine
Abstract
The analysis processes that take place in the phytotron, a mathematical model of the
phytotron, were carried out for further development of the automated control system using
the Internet of Things (IoT) technology. The functional-algorithmic scheme of the phytotron
and the algorithm of remote temperature control of this object are developed. The software
and hardware implementation of the control system for the phytotron is based on the
integrated Arduino board. Reads information from sensors, also developed an operator
interface in the form of a mobile application, in addition to recording the measured values in
the database on the server for further processing. It is possible to store files in the cloud and
remotely control processes from a mobile device. The software provides an address poll of
the sensor, which allows you to estimate the change in the controlled parameter at the
location of the sensor. The structural scheme of the electrical complex of the phytotron and
the scheme of control of this technological object with the use of IoT technologies are given.
Keywords 1
Internet of things, cloud technologies, platform, software, algorithm, phytotorn,
electrotechnical complex, interface, information control system.
1. Introduction
To study the development of plants, it is necessary to conduct constant phytomonitoring of the plant
and their development environment. To determine the influence of disturbing factors on plant
development, a system of phytomonitoring of technological parameters in the phytotron has been
developed. The developed system uses the approach of Internet of Things technology for remote
monitoring of the technological process and switching of connected devices of the electrical complex in
the chambers of phytotron cultivation. An effective solution to the problem of growing (producing)
agricultural products in modern conditions of agribusiness is achieved by introducing information and
control systems at production sites. In this regard, the problem arises of creating a hardware-software
complex based on modern automation tools. In recent years, new directions in automation systems and IT
have been actively developing - cloud technologies and the Internet of Things (IoT), which have found
successful application in agricultural production, given the length of control objects and their remoteness
from decision-making centers. Today, IoT is the most modern tool for industrial automation, which allows
remote monitoring of the state of an object (including biotechnical) and remote control of drive
mechanisms and devices located at the object.
2. Literary review and purpose of research.
Many researchers from Ukraine and other countries were engaged in the study of the problems of
the phytotron and greenhouses and the use of Internet-of-Things technology to control parameters.
Scientists from Belgium and Morocco R. A. Abdelouhahid, O. Debauche, S. Mahmoudi create a
personal phytotron at an affordable price thanks to a wide range of hardware, cloud computing and
Information Technology and Implementation ITI-2021, December 01–03, 2021, Kyiv, Ukraine
EMAIL: taraslendel@gmail.com (A. 1); nkiktev@ukr.net (A. 2);
ORCID: 0000-0002-6356-1230 (A. 1); 0000−0001−7682−280X (A. 2); 0000-0002-2120-1552 (A. 3)
©️ 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
251
new opportunities offered by the Internet of things (IoT) [1]. Taiwanese researchers Yu-Chun Chu
and Jer-Chia Chang in the chambers of the phytotron tested the temperature regimes, relative
humidity and illumination as environmental parameters for growing seedlings or plants in different
phases of development [2]. Phytotrons with various electronic control systems are also being created
to assess the effect of technological parameters on plants when breeding new varieties. One of them is
described in a study by Algerian scientists H. Adjerid, Y. Remram and M. Attari [3]. The researchers
presented an electronic control system that includes monitoring and control of air temperature,
relative humidity and lighting as environmental parameters. This made it possible to form a new
phytotron typology based on two growth phases in order to study the impact of climate change on
plants.
In milk production, animal health monitoring is carried out, which includes data tracking using IoT
tools. This allows you to know at what point in time you need to change the feed ingredients. There
are also technologies for monitoring the quality and quantity of feed grains and oil crops [4].
According to the author, IoT technology is best suited for tracking the location and feeding of animals
in a meadow or in a barn. Connecting a collar with sensors to cows allows continuous monitoring and
optimal nutrition planning.
Latin America is implementing the latest precision farming technologies, and this technology will
be included in AquaSim, a set of customizable IoT productivity tools [5]. The aquaculture division
Nutreco Skretting together with the Eruvaka company is implementing IoT in fish farming [5]. IoT
technologies in agriculture are intensively used in India, where, due to population growth, the
problem of food saturation is acute. The project described in the work of researchers L. Abhishek and
B. Rishi Barath [6] includes the automation of technological processes in agriculture, including the
measurement of soil moisture, so that the farmer can decide whether to use wet or dry crops
depending on the conditions. as well as water level measurement. In another project, described in the
work of Indian researchers K.R. Raghunandan, L.J. Quadras et al. [7], IoT technology is used in the
following technological processes:
- automation of irrigation - a system based on soil moisture and water level, measuring moisture,
temperature and dew point;
- lighting control - automation to save energy;
- security alarm using infrared radiation;
- sending from a sensor located on farmland, a report to the farmer using a notification system.
One of the options for applying the technologies was proposed by professors of the Institute of
Electrical and Electronics Engineers K.A. Patil and N.R. Keil [8]. A “Smart Agriculture Model Using
the Internet of Things” has been developed, which implements a real-time soil monitoring system,
monitors soil moisture content, acidity and temperature, and these values are used to deploy support
and decision-making systems. This system helps in identifying crop pests and diseases and sends
SMS alerts to the owner. The proposed architecture consists of three modules: client-side, server-side,
and farm-side. The standard Ubi-Sense Mote (M) sensor board is used to measure temperature,
humidity, barometric pressure and proximity. The data collected by Ubi-Sense Mote is then sent to
the server. The server part consists of a support and decision making system that sends the required
information received from the sensors to the client side, which consists of a web application and a
mobile application for Android. The disadvantage of this system is that no methodology for
improving irrigation facilities is proposed, and the mobile application is not available for iOS phones.
Another method, considered by P. Patil and A. Narhidi [9], involves the use of a soil moisture
sensor, which measures the value of the moisture content in the soil at fixed intervals. When the soil
moisture level is registered below the threshold value, an SMS notification is sent to the user. The
main disadvantage of using this method is that data is sent at a fixed time interval. Minimizing the
interval will result in excessive energy consumption, increasing the interval may damage the crop.
This system will be useful for monitoring the state of soil moisture on the farm, as well as for
controlling soil moisture by monitoring the water level in the water source and, accordingly, turning
on / off the motor for irrigation purposes and using the PIC16F877A and GSM SIM300 modem. The
system offers a soil moisture sensor in every location where moisture needs to be monitored. Another
proposed system is the "Intelligent irrigation system for automating the maintenance of field
conditions based on the Internet of Things", proposed by N. Rao and B. Sidhar in 2018 [10]. Two
sensors, a soil moisture sensor and a temperature sensor, are placed in the crop field. Data from these
sensors is collected using the Raspberry Pi microcontroller, a series of single-board minicomputers
originally developed in the UK for teaching in schools, but with widespread use.
252
The sensor readings are sent to the Raspberry Pi controller, in which the Apache web server is
configured. The Raspberry Pi also has a storage such as SQL database or container. The ZigBee
module is used to establish a communication channel between the sensor arrays and the server. The
farmer can access the field status server anytime, anywhere, thereby reducing labor and time.
Mmultishock communication has been implemented to increase the communication range. Data
from sensor arrays are transmitted through neighboring sensor matrices for further transmission to
their neighbors. The data is then sent to the database using WiFi, so the user of this system can track
changes and draw up an irrigation plan at his own discretion. The disadvantage of this method is that
no security protocols are implemented in the system.
IoT livestock management solutions make livestock monitoring more affordable than ever before.
Livestock monitoring solutions are based on portable sensors mounted on the body of animals [11].
These sensors can track heart rate, blood pressure, temperature, breathing rate, and even digestion and
send the data over the Internet to a central computer for further analysis. With the help of these
sensors, farmers can also track the location of individual farm animals, identify sick ones, and track
their optimal grazing regimes. This can help farmers respond quickly to an infected animal and stop
disease transmission to other animals in the herd.
Researchers from Ukraine A. Zhiltsov, I. Bolbot et al. in the article [12] substantiated
phytomonitoring in a greenhouse using non-contact visual assessment of plants. The basis of such an
assessment is the performance of photography of plants by a special electrical complex, after which
the stored images are recognized using wavelet analysis technology. The use of this photo technology
as a means of non-contact information makes it possible to assess the growth and condition of plants
in a greenhouse and predict their development using mathematical transformations, which will allow
us to estimate future crops. The authors have developed a recognition algorithm, it is used to
recognize biomass in the greenhouse space.
In the work of Ukrainian researchers V. Lysenko, T. Lendiel and D. Komarchuk [13], a hardware-
software subsystem for phytomonitoring in a greenhouse was implemented based on the LabVIEW
software environment and Arduino hardware support, and this subsystem was tested in industrial
production - JSC "Combine Teplichny" in the Kyiv region. It is shown that when growing vegetables,
along with the temperature characteristics of the environment, information about the temperature of
plants is important. The dependence of the temperature of plants on the illumination in the greenhouse
was analyzed, and an improved mathematical model of the greenhouse was obtained, suitable for the
formation of control actions, taking into account the spatial location of the control object. In a work
with the participation of the authors of this article [14], N. Kiktev, T. Lendiel and V. Osypenko
proposed using the Internet of Things technology in agricultural production, in particular, in the
production of feed. The work contains a combination of software and hardware solutions based on the
Arduino control board with mathematical models for optimizing the composition of feed according to
the criterion of maximum yield of a substance with nutritional restrictions on feed components.
Researchers from Qatar, Morocco and Canada A. Ouammi, Y. Achour et al. [15] presented a
comprehensive energy management system based on the centralized control of an intelligent
greenhouse. Such management allows optimizing and controlling the global indoor environment for
growing crops. The development is to implement a comprehensive predictive control (MPC) energy
management platform that takes into account the volatile behavior of renewable energy production,
the dynamics of energy and water storage, as well as uncertainties associated with climate conditions.
The authors propose a multi-purpose integrated optimization system for managing the operation of a
smart greenhouse, taking into account forecasts and updated data collected from an available network
of wireless sensors.
An interesting study by Turkish scientists M.A. Akkasha and R. Sokulu [16], who presented a
prototype consisting of MicaZ blocks, which are used to measure temperature, light, pressure and
humidity in greenhouses. The measurement data was provided via the Internet of Things. With this
system, farmers can manage their greenhouse from their mobile phones or computers connected to the
Internet. Canadian researchers M. Bozchalui and K.A Canizares in their article [17] presented a new
hierarchical approach to management and new mathematical models for optimizing greenhouses,
which are easily integrated into the energy center control system.
An article by Chinese researchers Yin Ding, Liang Wang et al. [18] proposes the use of intelligent
algorithms in modern agricultural production, which requires database support, which can be complex
253
and difficult to use in practice and requires a large amount of computation. A predictive model (MPC)
is proposed that can provide high-precision control operations at moderate complexity, and also
allows running optimization in a limited time interval, which improves accuracy. Other Chinese
researchers J. Hou, and Y. Gao [19] propose the development of a solar-based greenhouse greenhouse
sensor monitoring system. It transmits data using wireless equipment for receiving and sending
without installing wiring. Compared to conventional wireless technology, this system design
consumes less energy, costs less money and has a higher Internet bandwidth. Sensor nodes receive
solar energy and supply it to a wireless sensor network. This system uses the MSP430 microcontroller
with ultra-low power consumption and the nRF24L01 low-power network transmission chip to
minimize system consumption. Moreover, this system uses multilevel energy memory. It combines
energy management with energy transfer, which allows you to wisely use the energy collected by
solar panels. Thus, a self-managing energy supply system was created.
Romanian researchers R.-O. Gregory, A. Water et al. [20] offer temperature control of a
greenhouse heated by renewable energy sources. Based on the linearized model, a PID controller was
set up, which was used to control the internal temperature in the greenhouse.
The software and hardware implementation of the information management system as applied to
various biotechnical objects based on the Arduino integrated board and the LabView visual
programming environment is considered by the authors of this article in [21]. In addition to reading
information from sensors, an operator interface was also developed in the form of a web page, as well
as recording measured values in a database for further processing. Data is stored on a storage device
in the form of tables unified with data processing programs. It is possible to store files in the cloud
and remotely control technological processes.
The purpose of the study is to develop and implement a system of phytomonitoring of
technological parameters of cultivation in the phytotron and the ability to remotely switch the
connected devices of the electrical complex.
3. Research materials
3.1. Mathematical model of the phytotron
The mathematical model of the phytotron is based on the heat balance equations for the
greenhouse [22]. For a phytotron, it is assumed that its space is the temperature zone around the
perimeter, taking into account the design features of its growing chamber. According to the
parametric scheme of the equation of heat balance for each zone can be written as:
Qi = Qt + Qk + Qt + Qv + Qc, (1)
where Qi is the amount of heat in the phytotron chamber, J; Qt is the amount of heat from the heating
system, J; Qk is heat loss transmitted through the side walls, J; Qt is heat consumption transmitted
through the end walls, J; Qv is the amount of heat to heat the ventilation air, J; Qc - heat from radiation
lamps, J.
The amount of heat in the phytotron chamber depends on:
Qi C pV p p t р , (3)
where Сp is heat capacity of air, J / kg · ° С; p is air density, kg/m3; tp is air temperature, °C; Vp is the
volume of the phytotron chamber, m3.
The amount of heat given to the phytotron chamber by the heating system is determined by:
Qt k tp S t (t w,i t i ) , (4)
where ktp is heat transfer coefficient through the wall of the heating system pipe W/m·°C, St is heating
surface area, m2; tw,i is heater temperature, °C; ti is air temperature in the phytotron, °С.
The model also takes into account the effect of heat from radiation lamps, J., which is equal to: ,
Qс k s S k ,і Ocv (5)
where ks is the heat transfer coefficient due to additional lighting, W/m·°C; Sk,i is area of the base of
illumination, m2; Ocv is intensity of illumination, W/m2.
254
Heat consumption is determined taking into account all the end surfaces of the phytotron chamber,
which borders the corresponding temperature zone:
Qv k pz ( S b ,i S k ,i )(t i t z ) , (7)
where kpz is the heat transfer coefficient through the end surfaces of the phytotron chamber to the
external environment W/m2 · ° C; Sb,i is the area of the end surface in the chamber, m2; ti, tz is outdoor
air temperature, respectively, °C.
The functional-algorithmic scheme of the phytotron complex will look like Fig. 1.
t Heater Wt(s)
Сontrol
Fan motor
Element
φ Moisturizer Wφ(s)
EZ CO2 Valve WCO2(s)
L Lamps WL(s)
H Pump WH(s)
Figure 1: Functional-algorithmic scheme of the phytotron: EZ - reference element; Wt (s), Wφ (s),
Wco2 (s), WL (s), WH (s) - transfer functions of the control object in terms of temperature, humidity,
air pollution, lighting and irrigation.
3.2. Algorithm for remote temperature measurement
To study the development of plants in the management of the technological mode of plant growth,
I use phytochambers, in combination with all the equipment is a phytotron. The phytotron is a
chamber with the created artificial climate where it is possible to regulate temperatures, humidity and
gassiness of air, and also management of watering and lighting.
The control system operation algorithm is shown in Fig. 2. The system works as follows:
1) after the presentation of the power supply, the entire system is initialized, the critical value of
the time tk is entered;
2) the effective value of the time t is compared with the critical value of the time tk (the time
during which the entire technological process takes place);
3) measurement of technological parameters;
4) check the wireless connection, assign an ip-address;
5) when connected via wireless communication, the measured value is displayed;
6) waiting for the command; go to item 2;
8) if there is no wireless connection, the system goes into automatic mode;
9) after the transfer of the control action to the actuators, data is sent to the personal computer of
the general control system; go to item 2.
11) when the critical time is reached, the program ends.
255
The general algorithm of the specified is shown in Fig. 2. One of the most important features of
the ESP8266 is that it can not only connect to an existing Wi-Fi network and act as a web server, but
can also set up its own network, allowing other devices to connect directly to it and access it. to web
pages. This is possible because the ESP8266 can operate in three different modes: station mode,
access point mode and both first modes simultaneously.
Start
Initialization,
introduction of T
Assigning an IP
address
Measurement of T
Connection
request
Check the
connection Yes
No
End of the
Data output program
Figure 2: Algorithm for remote temperature (T) measurement
4. Research results.
During operation, the phytotron control system provides real-time data collection and processing
in the phytotron, plays the role of a controlling component of the parameters of plant
phytodevelopment and technological parameters of the microclimate. The set of hardware used in this
case - hardware and software environment of Arduino. Their diversity and availability have created
the conditions for the successful implementation of automation systems that operate on the basis of
Internet of Things technologies. The technological scheme of phytotron operation is made (Fig. 3):
K1 and K2 - 1st and 2nd phytochambers;
L1, L2 - lamps of the 1st and 2nd chambers;
C - LED backlight;
B1 and B2 - fans of the 1st and 2nd chambers;
H - pump; P - heater; G1 and G2 - humidifier 1st and 2nd;
O1 and O2 - light sensor (inclusions L1, L2);
T1 and T2 - air temperature sensors (inclusion P);
T3 and T4 - Plant temperature sensors (pyrometers);
256
T5 and T6 - substrate temperature sensor (DS18b20, DHT11);
F - humidity sensor (DHT 11) (inclusion G1, G2).
Figure 3: Schematic arrangement of sensors, actuators and regulators
The control of the phytotron electrical complex is divided into three hierarchical levels. The
structure of the electrical complex is presented in the following figure (Fig. 4). The phytoclimatic
regime is controlled according to the specified cultivation norms, where the daytime air temperature is
within 22..25° С; at night - 18..20° С; where the relative humidity should be within 60..70% and air
pollution is 350..450 ppm. The control process also provides for the study of the impact of the
environment on tomato plants, provides for the additional introduction of phytotemperature criteria
for plant development [6], according to which the plant temperature is equal to the air temperature.
The phytotron was mounted in the laboratory of the Department of Automation and Robotic
Systems. academic І.І. Martynenko (Figs. 5, 6). The monitoring system is based on the Arduino Uno
and the W5100 controller. A web-server was built for graphical display of remote client data,
obtaining measured data from temperature, pressure, humidity sensors and the ability to switch the
relay to which the devices of the electrical complex are connected (Fig. 7). The server program is
written in the Arduino IDE development environment. A Wi-Fi wireless network is also used to allow
wireless access to the specified web server. Screenshot of the web server configuration screen show in
Fig. 8. When the client requests the server's address in the internal network (http://10.11.0.105), the
server contacts the Arduino Uno controller, which forwards the measured data to the browser. The
program also provides lighting of the relay switching buttons for switching on and off the components
of the electrical complex. Active monitoring of plant development also allows to study the influence
of disturbing factors on plant development and the quality of the original vegetable products.
In the project under consideration, the Arduino MEGA2560 + WiFi R3 controller from RobotDyn
is used for remote control [23]. In the process of project development, the model "Arduino ESP8266"
is used which has all the necessary technical means and external elements for connection (Fig. 1, b).
The main idea of using the board is that the switches can be used to configure the interaction of its
three components in different ways: the Atmega2560 chip, the ESP8266EX chip, and the CH340G
USB-TTL converter [24].
257
Upper level
• monitoring of parameters by the operator;
• implementation of technological equipment control
algorithms;
• saving data from primary converters to a database.
Lower level Technical equipment
• direct control of technological • сhannels of control of
equipment; technological parameters;
• survey of primary converters. • primary converters;
Figure 4: The structure of the electrical complex of the phytotron
Figure 5: Appearance of the workplace of the phytotron operator
5. Discussion
Remote control technologies for other objects are considered by Ukrainian authors N. Kiktev, H.
Rozorinov, N. Chichikalo et al. [25]. In particular, the technological scheme of the information-
measuring system for determining the ash content of coal has been improved, the algorithm and
software interface have been worked out, which will improve the quality of mine coal. The task of
creating a video surveillance system based on the state of a mining and technological facility is solved
using the example of a conveyor belt in order to further transfer information to the controller.
For decision-making in control systems, the mathematical apparatus described in the work of
Ukrainian researchers O. Oletsky, E. Ivohin [26] can be applied, in particular, the evaluation and
comparison of alternatives in decision-making problems based on a certain class of matrices and
Markov chains.
In the future, the authors plan to conduct a series of experiments in an industrial greenhouse and
work out remote control of individual processes using the Internet of things technology.
6. Conclusions
A phytotron model for the study of plant development has been developed and implemented. The
structure of the control system has been created, the functional-algorithmic system of the control
258
object has been built and the system of phytomonitoring of plant growing parameters with the use of
Internet of Things technology has been implemented.
A web-server was built for graphical display of remote client data, obtaining measured data from
sensors of temperature, pressure, humidity and the ability to switch the relay to which the devices of
the electrical complex are connected.
Figure 6: Appearance of the phytotron chamber
Figure 7: The structure of the control system
259
Figure 8: Screenshot of the web server configuration screen
7. References
[1] Abdelouhahid, R. A., Debauche, O., Mahmoudi, S., Marzak, A., Manneback, P., & Lebeau, F.
(2020). Open phytotron: A new IoT device for home gardening. Paper presented at the
Proceedings of 2020 5th International Conference on Cloud Computing and Artificial
Intelligence: Technologies and Applications, CloudTech 2020,
doi:10.1109/CloudTech49835.2020.9365892.
[2] Chu, Y. -., & Chang, J. -. (2020). Regulation of floral bud development and emergence by
ambient temperature under a long-day photoperiod in white-fleshed pitaya (hylocereus undatus).
Scientia Horticulturae, 271 doi:10.1016/j.scienta.2020.109479.
[3] Adjerid, H. E., Remram, Y., & Attari, M. (2020). Development of an electronic system for the
control of climatic parameters in a phytotron. Paper presented at the CCSSP 2020 - 1st
International Conference on Communications, Control Systems and Signal Processing, 417-421.
doi:10.1109/CCSSP49278.2020.9151598.
[4] A. Einstein-Curtis. “What role exists for IoT technologies in the feed industry.”
FeedNavigator.com (2018). URL: https://www.feednavigator.com/article/2018/05/31/what-role-
exists-for-iot-technologies-in-the-feed-industry
[5] Feed Update: Latest insights from the global feed industry (2018). URL:
https://www.allaboutfeed.net/Home/General/2018/5/Feed-Update-Latest-insights-from-the-
global-feed-industry-283164E/
[6] L. Abhishek, and B. Rishi Barath. “Automation in Agriculture Using IOT and Machine
Learning.” International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075, Volume-8, Issue-8, June (2019): 1520-1524. DOI: 10.1016/j.procs.2020.03.440
[7] K.R. Raghunandan, L.J. Quadras, S. Gurunandan, S.S. Karthik. “Usage of Internet of Things in
Agriculture Automation.” International Journal of Computer Trends and Technology (IJCTT),
Vol. 58, Issue 1, April (2018): 35-39. DOI: 10/14445/22312803/IJCTT-V58P106
[8] K.A. Patil, and N.R. Kale. "A Model of Smart Agriculture Using IoT." 2016 International
Conference on Global Trends in Signal Processing, Information Computing and Communication
(ICGTSPICC), IEEE, Dec. (2016): 543 – 545. DOI: 10.1109 / ICGTSPICC.2016.7955360.
[9] Prachi Patil, Akshay Narkhede, Ajita Chalke, Harshali Kalaskar, and Manita Rajput. “Real Time
Automation of Agricultural Environment.”, International Conference for Convergence for
Technology-2014, 6-8 April 2014, Pune, India, pp. 1-4. DOI: 10.1109/I2CT.2014.7092040
260
[10] Nageswara Rao and B. Sridhar “IoT based smart cropfield monitoring and automation irrigation
system ” 2nd International Conference on Inventive Systems and Control (ICISC), IEEE, Jan.
2018, Pages: 478 – 483.
[11] S. Coppol. “How the Internet of Things (IoT) Is Helping the Agriculture Sector.”
colocationamerica.com (2019). URL: https://www.colocationamerica.com/blog/how-the-internet-
of-things-iot-is-helping-the-agriculture-sector
[12] Lysenko, V., Zhyltsov, A., Bolbot, I., Lendiel, T., & Nalyvaiko, V. (2020). Phytomonitoring in
the phytometrics of the plants. Paper presented at the E3S Web of Conferences, Volume 154, art.
no.07012, doi:10.1051/e3sconf/202015407012.
[13] V. Lysenko, T. Lendiel and D. Komarchuk, "Phytomonitoring in a Greenhouse Based on
Arduino Hardware," 2018 International Scientific-Practical Conference Problems of
Infocommunications. Science and Technology (PIC S&T), 2018, pp. 365-368, doi:
10.1109/INFOCOMMST.2018.8632030.
[14] Kiktev, N., Lendiel, T., Osypenko, V. (2021). Application of the internet of things technology in
the automation of the production of compound feed and premixes. Paper presented at the CEUR
Workshop Proceedings, vol 2833, pp. 124-133. http://ceur-ws.org/Vol-2833/
[15] Ouammi, A., Achour, Y., Dagdougui, H., & Zejli, D. (2020). Optimal operation scheduling for a
smart greenhouse integrated microgrid. Energy for Sustainable Development, 58, 129-137. DOI:
10.1016/j.esd.2020.08.001.
[16] Akkaş, M. A., & Sokullu, R. (2017). An IoT-based greenhouse monitoring system with micaz
motes. Paper presented at the Procedia Computer Science, 113 603-608. DOI:
10.1016/j.procs.2017.08.300
[17] Bozchalui, M. C., Cañizares, C. A., & Bhattacharya, K. (2015). Optimal energy management of
greenhouses in smart grids. IEEE Transactions on Smart Grid, 6(2), 827-835.
DOI:10.1109/TSG.2014.2372812
[18] Ding, Y., Wang, L., Li, Y., & Li, D. (2018). Model predictive control and its application in
agriculture: A review. Computers and Electronics in Agriculture, 151, 104-117. DOI:
10.1016/j.compag.2018.06.004
[19] Hou, J., & Gao, Y. (2010). Greenhouse wireless sensor network monitoring system design based
on solar energy. Paper presented at the International Conference on Challenges in Environmental
Science and Computer Engineering, CESCE 2010, , 2 475-479. doi:10.1109/CESCE.2010.274
[20] Grigoriu, R.., Voda, A., Arghira, N., Calofir, V., & Iliescu, S. S. (2016). Temperature control of
a greenhouse heated by renewable energy sources. Paper presented at the Joint International
Conference - ACEMP 2015: Aegean Conference on Electrical Machines and Power Electronics,
OPTIM 2015: Optimization of Electrical and Electronic Equipment and ELECTROMOTION
2015: International Symposium on Advanced Electromechanical Motion Systems, 494-499.
DOI:10.1109/OPTIM.2015.7427009
[21] N. Kiktev; T. Lendiel; N. Pasichnyk; D. Khort; A. Kutyrev. Using IoT Technology to Automate
Complex Biotechnical Objects. 2021 IEEE 8th International Conference on Problems of
Infocommunications, Science and Technology (PIC S&T), 05-07 October 2021, Kharkiv, pp.
DOI: 10.1109/PICST54195.2021.9772218
[22] Draganov B.Kh., Kuznetsov A.V., Rudobashta S.P. Heat engineering and application of heat in
agriculture. – M.: Agropromizdat, 1990. – 463 p. 82.
[23] Developer board Arduino MEGA2560 WiFi R3 from RobotDyn. URL:
https://arduino.ua/prod2039-plata-razrabotchika-arduino-mega2560wifi-r3-ot-robotdyn
[24] Review of NodeMcu v2 board on ESP8266-12E. URL: https://robotchip.ru/obzor-platy-
nodemcu-v2-na-esp8266-12e/
[25] N. Kiktev; N. Chichikalo; H. Rozorinov; R. Filippov; D. Khort. Infocomunication Technology
for Determination of Coal Ash-Content on the Conveyor Line. 2018 International Scientific-
Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T), 9-12
Oct. 2018, Kharkiv, Ukraine. DOI: 10.1109/INFOCOMMST.2018.8632108
[26] O. Oletsky, E. Ivohin. Formalizing the Procedure for the Formation of a Dynamic Equilibrium of
Alternatives in a Multi-Agent Environment in Decision-Making by Majority of Votes. Cybern
Syst Anal Vol.57, 47-56 (2021). DOI: 10.1007/s10559-021-00328-y
261