THE USA JOURNALS
THE AMERICAN JOURNAL OF ENGINEERING AND TECHNOLOGY (ISSN
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2689-0984)
VOLUME 06 ISSUE10
119
https://www.theamericanjournals.com/index.php/tajet
PUBLISHED DATE: - 21-10-2024
https://doi.org/10.37547/tajet/Volume06Issue10-13
PAGE NO.: - 119-125
DIGITAL TOOLS FOR MONITORING AND
MANAGEMENT IN AGRICULTURAL
PRODUCTION
Kantemir Vologirov
Chief Developer at Marketplace-Technologies LLC, Nalchik, Russia
INTRODUCTION
In recent years, the digitalization of agricultural
production has become increasingly relevant
against the backdrop of global changes in the
agribusiness sector. Technological advancements
open new opportunities for monitoring and
managing agricultural processes, ensuring more
efficient resource use and increased yields. Digital
tools such as mobile applications, drones, and
satellite data enable farmers and agronomists to
monitor field conditions in real-time, significantly
improving decision-making processes. The use of
such technologies has become an important
element of competitiveness in agriculture,
especially in the context of climate change and the
growing demand for food security.
The relevance of this research is driven by the
increasing need to optimize agricultural processes,
which requires the implementation of innovative
monitoring and management methods. In the face
of global climate changes and the depletion of
natural
resources,
enhancing
agricultural
efficiency and minimizing the impact of external
factors on agricultural processes have become
increasingly significant. The adoption of digital
solutions can not only increase yields but also
reduce resource costs, making them a necessary
component of sustainable development in the
agricultural sector.
This work aims to study digital tools for
monitoring and management in agricultural
production and their impact on enhancing the
efficiency and sustainability of agricultural
processes.
RESEARCH ARTICLE
Open Access
Abstract
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1. Mobile Applications for Field Monitoring
In the agricultural sector, there is currently rapid
development among large enterprises such as
agribusiness holdings, which manage extensive
areas of agricultural land. Modern technologies,
such as satellite monitoring and the use of drones,
are being actively applied for field diagnostics.
These methods allow for the rapid acquisition of
accurate data. Among other tools, leaf diagnostics
and soil analysis are also actively used.
High-resolution satellite images, which are used
for diagnosing crop conditions, provide farmers
with the ability to analyze field status using
spectral cameras. Spectral data enable the
calculation of vegetation indices, such as NDVI,
which is widely used in agriculture. Satellite data
not only help assess the current state of crops but
also analyze the development dynamics of fields
over the past years. This allows agronomists to
adjust crop rotation and identify errors from
previous seasons to develop more effective work
plans.
An undeniable advantage of satellite monitoring is
the capability for retrospective analysis due to
image archiving. This aids in analyzing the history
of yield changes and other field indicators over
extended periods. However, it is important to
consider the dependence of data accuracy on
weather conditions, such as cloud cover, and
limitations on the frequency of imaging, which is
typically conducted weekly.
The practical application of data obtained through
satellites and drones requires knowledge of
agronomy and geoengineering. The use of this data
is effective at all stages of the production cycle,
starting from assessing soil conditions before
planting and ending with yield forecasting before
harvest.
During the initial monitoring phase, the state of the
soil and the terrain of the plot are assessed, helping
to determine optimal cultivation methods. At the
seedling stage, the density and uniformity of crops
are analyzed, allowing for the identification of
areas with losses and the implementation of
appropriate measures.
Subsequently, fertilizer application is monitored,
and weed control is conducted, as weeds are one of
the main causes of yield loss. Drone images not
only assess the concentration of weeds but also
identify their types, aiding in the selection of the
most suitable herbicides.
Leaf diagnostics and soil analysis are important
tools for assessing crop conditions and
determining the necessary measures for
fertilization. Leaf diagnostics help evaluate the
chemical composition of plant tissue, while soil
analysis identifies the fertility level and
contamination of the plot.
Thus, the use of modern field monitoring
technologies contributes to the effectiveness of
agronomic practices, improving yields and
optimizing resource use. Digital data allow farmers
to make more informed decisions. For instance,
creating a unified database for fields that includes
information on previous yields and agrochemical
characteristics helps improve planning and reduce
losses. Additionally, using yield maps allows for
the optimization of fertilizer use, which is
particularly relevant given the rising costs.
Digital technologies also provide farmers with the
ability to quickly assess crop conditions. For
example, through geospatial analysis, problematic
areas can be identified promptly, allowing for the
adjustment of agronomic practices. Monitoring
systems, such as the Cropwise platform, provide
nearly ready data on plant conditions, enabling
farmers to respond swiftly to changes and make
informed management decisions. Table 1 below
describes the functionality of mobile applications
for monitoring field conditions.
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Table 1. Functionality of mobile applications for monitoring the state of fields [5].
Functionality
Description
Soil Moisture
Monitoring
Applications receive real-time data from sensors regarding soil moisture,
helping to optimize irrigation.
Temperature
Monitoring
Applications track current and forecasted temperatures, enabling the planning
of agronomic activities.
Plant Condition
Analysis
Using data from drones and satellites, applications assess plant health,
including greenness and stress levels.
Light Level Control
Applications measure sunlight levels affecting plant growth and provide
agronomic recommendations.
Satellite Data
Processing
Applications integrate with satellite systems to obtain field images and
analyze conditions over large areas.
Weather Condition
Notifications
Applications send alerts about weather changes (rain, drought, frost), helping
to take prompt action.
Irrigation
Management
Applications allow remote management of irrigation systems based on soil
moisture data and weather forecasts.
Pest and Disease
Detection
Through image analysis and sensor data, applications identify pests or
diseases at early stages.
Yield Forecasting
Applications use historical data and current indicators to create forecasts of
expected yields.
Geolocation and
Field Mapping
Mobile applications provide maps of fields indicating current conditions and
various treatment zones.
Resource
Management
Applications help track the use of fertilizers, herbicides, and other resources,
increasing their efficiency.
Reporting and
Analytics
Applications generate reports based on collected data and offer
recommendations for improving fieldwork.
Compatibility with
Drones and Sensors
Applications integrate with drones, IoT sensors, and other devices for more
accurate field monitoring.
Thus, digital solutions assist farmers not only in
managing their fields more effectively but also in
conserving resources by making more accurate
and informed decisions.
2. Mobile Solutions for Resource and
Operations Management in Fields
Digital solutions for the agribusiness sector are
becoming key tools for ensuring high productivity
and accuracy in agricultural management. Modern
applications allow for the effective tracking of
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production processes in real-time, minimizing
human error and significantly reducing the risks of
mistakes. They process vast amounts of data,
contributing to increased productivity of
agricultural lands.
The functional capabilities of these applications
include:
●
comprehensive monitoring of crop and land
conditions, soil analysis, fertilizer application,
management of planting campaigns, and harvest
collection;
●
use of vegetation maps;
●
satellite monitoring of field properties;
●
monitoring of pest and weed infestations;
●
mapping of land plots, sampling of soil and
plants for phytopathological and agrochemical
studies;
●
monitoring of harvest collection, from
loading in the field to storage.
These digital tools allow for the automation of
many routine operations, reducing time and labor
costs. The applications facilitate process
optimization, significantly lowering management
expenses for agricultural operations.
Some technologies enable enterprises to monitor
the condition of their equipment and conduct
preventive maintenance. This is particularly
relevant for essential production assets, such as
technological lines, boilers, and electrical
networks. Specialists conducting inspections focus
on inventory management and diagnostics,
identifying defects, and troubleshooting, which
allows for quick responses to any technical issues.
Typically, such inspections at enterprises are
organized manually, which can lead to time and
resource losses. Traditional methods using
notebooks and logs often result in errors and
delays. To address these shortcomings, mobile
solutions, such as applications for monitoring
equipment conditions, are increasingly being used
to automatically record data and resolve issues
more quickly. If discussing the elements of this
system, they are reflected in Table 2.
Table 2. Elements of the mobile system [7].
Element
Purpose
Suitable Automation
Solution
Data Collection
Terminal
The device is used as a mini-computer for
data entry during inspections and for sending
data to external accounting programs
Any data collection
terminal from the catalog or
an Android smartphone
Field Worker
Application
It records information about fixed assets,
manages work orders, plans routes, and more DM.TOIR
Information System
(Accounting Program)
It allows for the accounting of fixed asset
objects and repair activities, registers defects,
plans teamwork, and creates orders. It
integrates with the application on the data
collection terminal, sends tasks to it, and
remotely receives data.
"1C
Enterprise Management"
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Thus, such applications ensure comprehensive
monitoring of crop conditions, soil analysis, pest,
and weed monitoring, as well as equipment
condition
management,
and
preventive
maintenance. The integration of satellite data,
vegetation maps, and other information sources
contributes to more effective management of
agricultural
operations
and
increased
productivity.
3. Application of Mobile Technologies for Yield
Analysis and Forecasting: The Case of
AgroMonitor
The application of mobile technologies for yield
analysis and forecasting has become an important
aspect of agricultural digitalization. In recent
years, the rapid development of mobile
applications and digital solutions has significantly
enhanced the efficiency of managing agricultural
processes. The use of mobile technologies not only
simplifies access to data but also enables timely
decision-making based on the information
obtained. This section describes the AgroMonitor
project
—
an application that enhances the
efficiency and sustainability of agricultural
operations
through
modern
technologies.
AgroMonitor provides farmers with digital tools
for monitoring, managing, and analyzing
agricultural resources. The application allows
users to receive real-time data on field conditions,
manage irrigation and fertilization, and forecast
yields. It integrates with various data sources, such
as sensors, drones, satellite imagery, and
meteorological
services,
ensuring
precise
management of agricultural processes.
One of the key advantages of this application in
agriculture is its ability to integrate with various
data sources. This data includes information on
soil conditions, moisture levels, nutrient content,
and
weather
forecasts,
enabling
timely
adjustments to crop management actions.
The use of this application also facilitates the
automation of yield forecasting processes.
Through machine learning algorithms and the
analysis of historical data, farmers can predict
potential yield volumes, taking into account the
influence of climatic conditions, soil types, and
applied agronomic methods. This significantly
enhances the accuracy of forecasts and minimizes
risks associated with crop failures or surplus
production.
Additionally, the use of mobile applications
streamlines
interactions
among
various
participants in the agricultural process. Farmers
can exchange information in real-time with
agronomists, consultants, and suppliers, which
accelerates decision-making and supports more
flexible resource management. Thus, mobile
technologies are becoming an essential tool for
increasing yields, improving planning, and
optimizing costs in the agricultural sector. Table 3
describes the capabilities of mobile technologies
for yield analysis and forecasting.
Table 3. Possibilities of mobile technologies for yield analysis and forecasting
[8].
Application Aspect
Description
Real-Time Data
Collection
Mobile technologies enable agronomists and farmers to collect data from
fields in real-time using sensors, drones, and GPS devices. This includes
monitoring soil conditions, moisture, temperature, and light levels.
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Use of Satellite Data
Mobile applications integrate with satellite monitoring systems to obtain
data on field conditions, plant greenness, and other indicators, aiding in
yield forecasting.
AI and Machine
Learning-Based
Forecasting
Mobile applications utilize artificial intelligence algorithms to analyze
collected data and create yield forecasting models based on climatic
conditions, agronomic practices, and historical data.
Irrigation
Management
Through mobile applications, farmers can monitor irrigation systems and
optimize water usage based on soil conditions and weather data,
enhancing crop cultivation efficiency.
Disease and Pest
Analysis
Mobile applications enable the detection of early signs of diseases and
pest invasions through images from drones or smartphones, helping to
prevent yield reduction.
Weather Condition
Monitoring
Mobile applications provide accurate weather forecasts and
recommendations for agronomic practices, assisting in better planning for
planting, fertilization, and harvesting.
Yield Forecasting
Based on collected data, mobile applications can predict yield levels by
analyzing climatic factors, soil conditions, and the current state of plants.
Integration with
Financial Systems
Mobile technologies can integrate with platforms that help farmers
forecast financial outcomes based on expected yields and production
costs.
Feedback and
Recommendations
Mobile applications provide personalized recommendations for
optimizing field operations based on data analysis, improving processes,
and increasing yields.
Resource and
Inventory
Management
Mobile technologies enable tracking and management of fertilizer, seed,
and other resource usage, facilitating more accurate planning of
agronomic practices and reducing costs.
Based on the above, it can be stated that the
application of mobile technologies for yield
analysis
and
forecasting
improves
the
management of agricultural processes by
providing farmers and agronomists with access to
real-time data and the ability to make timely
decisions. The automation of the forecasting
process using machine learning algorithms
minimizes risks associated with yield fluctuations
and promotes more effective planning and
resource
management.
Modern
mobile
applications, such as AgroMonitor, enable
agronomists and farmers to obtain real-time data
from sensors, drones, and satellites. This is
achieved through integration with various data
sources, such as sensors, drones, satellite imagery,
and meteorological services, ensuring precise
management of agricultural processes.
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CONCLUSION
Digital technologies play a crucial role in
modernizing agriculture, enabling efficient
management of production processes and
minimizing risks. Mobile solutions that integrate
data from various sources, such as drones,
satellites, and sensors, provide farmers and
agronomists with tools for timely analysis and
decision-making. The implementation of such
technologies enhances the monitoring of field
conditions and resources, ultimately contributing
to increased yields and the sustainability of
agricultural production.
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