Інтелектуально інформаційна система соціально-економічної інфраструктури міста
Urban development is an important problem that can be solved with the help of intelligent information systems. Such systems ensure efficient management of the city’s diverse infrastructure. The researchers developed a concept of such an information system based on a conceptual model and using data f...
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The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
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| author | Lipianina-Honcharenko, Khrystyna Bodyanskiy, Yevgeniy Sachenko, Anatoliy |
| author_facet | Lipianina-Honcharenko, Khrystyna Bodyanskiy, Yevgeniy Sachenko, Anatoliy |
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| description | Urban development is an important problem that can be solved with the help of intelligent information systems. Such systems ensure efficient management of the city’s diverse infrastructure. The researchers developed a concept of such an information system based on a conceptual model and using data flow for intelligent decision-making. The system was tested for 1460 days in the city of Ternopil. The modelling results showed that the city’s central area is stable, with 50% of enterprises in the “growing” state and 70% of people in the “satisfactory” state. People often move to the northeastern and western zones due to higher levels of comfort and more affordable housing. However, the total distance of car trips has increased by 249%, negatively impacting the environment. The condition of enterprises in other zones is less stable with lower “growth” indicators, but there are zones with “stable” and “satisfactory” conditions. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2023.3.08 |
| first_indexed | 2025-07-17T10:28:22Z |
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Khrystyna Lipianina-Honcharenko, Yevgeniy Bodyanskiy, Anatoliy Sachenko, 2023
108 ISSN 1681–6048 System Research & Information Technologies, 2023, № 3
TIДC
ПРОБЛЕМНО І ФУНКЦІОНАЛЬНО
ОРІЄНТОВАНІ КОМП’ЮТЕРНІ СИСТЕМИ
ТА МЕРЕЖІ
UDC 004.94
DOI: 10.20535/SRIT.2308-8893.2023.3.08
INTELLIGENT INFORMATION SYSTEM OF THE CITY'S
SOCIO-ECONOMIC INFRASTRUCTURE
KHRYSTYNA LIPIANINA-HONCHARENKO, YEVGENIY BODYANSKIY,
ANATOLIY SACHENKO
Abstract. Urban development is an important problem that can be solved with the
help of intelligent information systems. Such systems ensure efficient management
of the city’s diverse infrastructure. The researchers developed a concept of such an
information system based on a conceptual model and using data flow for intelligent
decision-making. The system was tested for 1460 days in the city of Ternopil. The
modelling results showed that the city’s central area is stable, with 50% of enter-
prises in the “growing” state and 70% of people in the “satisfactory” state. People
often move to the northeastern and western zones due to higher levels of comfort
and more affordable housing. However, the total distance of car trips has increased
by 249%, negatively impacting the environment. The condition of enterprises in
other zones is less stable with lower “growth” indicators, but there are zones with
“stable” and “satisfactory” conditions.
Keywords: modelling, information system, socioeconomic infrastructure, city.
INTRODUCTION
In recent years, studies of economic infrastructure at various levels of the coun-
try's socio-economic system have been actively conducted. These studies have led
to the synthesis and systematization of knowledge about the economic infrastruc-
ture of states, regions and enterprises. This allowed us to reveal its essence and
explain the patterns and cause-and-effect relationships at different levels of the
economic system.
Recognition of the importance of the social component in the economic in-
frastructure of the state and regions led to the introduction of the category "socio-
economic infrastructure". This is because the growth of activity and efficiency of
economic entities is not the main goal, but should contribute to improving the
welfare of the population through increased wages, social assistance and im-
proved quality of social services.
Socio-economic infrastructure is a prerequisite for the stability and effi-
ciency of the socio-economic system at any level. In particular, cities play an im-
portant role in the country's economy due to their industrial, scientific and techni-
cal potential, financial and commodity markets, and the formation of decisions
Intelligent information system of the city's socio-economic infrastructure
Системні дослідження та інформаційні технології, 2023, № 3 109
that determine the vectors of socio-economic development of regions and the
state.
Therefore, it is necessary to develop an intelligent information system of the
city's socio-economic infrastructure to automate optimal decisions on the develop-
ment of the city's socio-economic infrastructure. In addition, such a system will
provide an opportunity to monitor the state of the city's infrastructure online, re-
spond quickly to problems and ensure their effective resolution.
ANALYSIS OF LITERATURE SOURCES
Article [1] explains the lexical and economic meaning of the term economic secu-
rity. To assess [2] the level of economic infrastructure, an integrated approach is
proposed, which consists in combining a number of indicators into a single inte-
gral indicator that summarizes data on the level of sustainable development of an
enterprise, which allows it to be used both in operational management and in
strategy. A resource-functional model of security (consisting of partial indicators
and components of economic security of business) was developed [3] and a re-
source-functional approach to calculations was also applied. A quantitative as-
sessment of the level of financial solvency of countries based on the use of multi-
dimensional methodological tools for assessing financial indicators of the
country's development was carried out [4], which leads to the construction of ap-
propriate integral security indices. Unlike other methods of assessing the level of
security, the proposed approach makes it possible to determine not only the inte-
grated level of the financial component of economic security, but also to calculate
the quantitative thresholds of financial indicators aggregated in the integral index
(foreign exchange reserves, external debt per capita, changes in the official ex-
change rate of the local currency, budget deficit/surplus to GDP); going beyond
the thresholds is a signal of increased risk and lack of solvency.
The article [5] investigates the problems of organizing an intelligent system
for managing complex socio-economic processes, defines its levels of intellectual
development, proposes stages of intellectualization, and demonstrates the effec-
tiveness of applying these solutions in practical tasks.
The article [6] assessed user satisfaction with the electronic social security
system (SSES) as a widely used system in Iran. In [7], the Hans-Böckler-Stiftung
and its research unit "Future Jobs" present a revised plan for Enzo Weber's DSS
model. DSS addresses the problem of serious gaps in social security for platform
workers. The model envisages that platforms around the world implement a digi-
tal mechanism to transfer a certain proportion of each agreed remuneration to a
global DSS account for the platform worker. The DSS account collects the contri-
butions generated globally and transfers them on a regular basis to the social secu-
rity system of the country where the platform worker is located. Article [8] dis-
cusses the principles of building intelligent decision support systems of situational
type for innovative development of megacities' infrastructure.
The article [9] provides new insights, develops a conceptual framework, and
identifies promising research questions by putting local government AI systems
under the microscope through the lens of responsible urban innovation.
The article [11] proposes a new conceptual framework for IDSS for disaster
management, with a particular focus on forest fires and cold/heat waves. IDSS
Khrystyna Lipianina-Honcharenko, Yevgeniy Bodyanskiy, Anatoliy Sachenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 3 110
uses big data collected from APIs and AI to help decision makers make faster and
more accurate decisions.
The article [12] explores the impact of governance on sustainability and re-
flects the impact of ICTs on decision-making by improving policy effectiveness,
accountability and transparency in urban systems. The paper also presents con-
ceptual system models of the cognitive city and energy behaviour, including three
sub-levels: human-institutional, physical, and data. It proposes integrated concep-
tual models to improve the efficiency of energy systems in complex and uncertain
environments, facilitate the resolution of energy consumption problems, and sup-
port capacity development at the individual, social and technical levels to improve
future energy management.
The article [13] was based on a synthesized and aggregated literature review
to build a new conceptual framework. The literature review revealed additional
existing smart city frameworks, including city services (essential services, nones-
sential services, and complementary services); city resources (superstructure, in-
frastructure, infostructure); city architecture (enterprises); and city goals (livabil-
ity, performance, and sustainability). This study contributes to a broader
understanding of the smart city reference model for Indonesia and other developing
countries.
The above-mentioned works mostly assess economic or social infrastructure
as a separate system. Few works consider the socio-economic infrastructure as an
information system (analogues).
In this regard, the purpose of this article is to develop the concept of an intel-
ligent information system for the provision of socio-economic infrastructure of
the city.
The developed intelligent information system for the provision of socio-
economic infrastructure of the city differs from its analogues [5, 7, 8, 9, 12] in
that it takes into account qualitative and quantitative indicators. This system can
automate the distribution of powers between the state and regional governments
in the development of master plans for the development of cities in the country,
social programmers and other documents aimed at improving the quality of life of
the population. In the future, this intelligent information system can be used as a
basis for the development of other systems for similar purposes.
CONCEPT OF AN INTELLIGENT INFORMATION SYSTEM FOR THE CITY'S
SOCIAL AND ECONOMIC INFRASTRUCTURE
To ensure the socio-economic infrastructure of a city, an intelligent information
system (Fig. 1) should contain at least four main levels of infrastructure: eco-
nomic, social, environmental, and socio-political. To achieve this goal, it is im-
portant to take into account both quantitative and qualitative indicators. Let us
consider each level separately.
he social sphere includes people's attitudes towards culture, art, and tourism
[18, 19], as well as an assessment of personal safety, the education system and
personal education, the healthcare system and personal health, amenities and
living conditions [16], and transport.
Intelligent information system of the city's socio-economic infrastructure
Системні дослідження та інформаційні технології, 2023, № 3 111
Intelligent information
system for the city's socio-
economic infrastructure
Quantitative
indicators Qualitative indicators
Ecological safety
Social security
Environmental assessment
situation
Assessment of the
security system
health and own
health
Evaluation of the
education system and
own education
Personal assessment
security
Attitude to culture,
art, tourism
Assessment of
landscaping and
living conditions
Performance evaluation
transport
Economic security
Sociopolitical security
Assessment of material
opinions
Assessment of the
situation regarding
employment
Assessment of the
sociopolitical situationSocial well‐being
Assessment of
economic stability
Information security
assessment
Fig. 1. The concept of an intelligent information system for the city's socio-economic
infrastructure
The importance of the environmental sphere for a person is an assessment of
the current environmental situation in the city.
As for the economic sphere, a city resident can assess economic stability
[17], their financial situation and the employment situation.
Today, during the period of military aggression in Ukraine, socio-political
security is becoming important for everyone, and every city resident can assess
the socio-political situation, information security and personal social well-being.
Let's take a closer look at the structure of the data flow in the intelligent in-
formation system for the city's socio-economic infrastructure (Fig. 2).
Data will be collected based on surveys of residents, as well as on the basis
of collected statistical indicators and sensor data. The latter is important for study-
ing the city's environmental infrastructure.
All quantitative data will undergo preliminary processing and will be stored
in the relevant databases. In the case of surveys, after collecting data into the da-
tabase, it needs to be processed using intelligent methods to give it quantitative
values.
Khrystyna Lipianina-Honcharenko, Yevgeniy Bodyanskiy, Anatoliy Sachenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 3 112
Database
of
answers
Database
of
statistical
indicators
Database
of sensors
Residents
of the city
Statistical
Office
Sensors Data cleaning
Data
cleaning
Intelligent
processing Output
of results
Test
database
Training
databaseSocial
Database
Database of
Environmental
Economic
Database
Sociopolitical
Database
Training
database
Intelligent
processing
Training
database
Intelligent
processing
Training
database
Intelligent
processing
Training
database
Intelligent
processing
Poll
Intellectual
processing
Calculation of
the
accuracy
of the result
Fig. 2. Data flow in an intelligent information system for the provision of the city's socio-
economic infrastructure
All data is then transferred to the databases of the four levels of socio-
economic infrastructure. At each level, intelligent data processing is carried out,
the results of which are transferred to a common training database. At the same
time, data from the databases of the four levels of socio-economic infrastructure
are transferred to a common test database.
The main intellectual processing is carried out on the common database, af-
ter which the accuracy is calculated relative to the common test database. Finally,
the results are displayed.
The presented conceptual model of an intelligent information system for en-
suring the socio-economic infrastructure of the city and the structure of the data
flow in it makes it possible to monitor threats to society in the context of socio-
economic infrastructure in real time. The developed conceptual model can be part
of a smart city [10].
EXPERIMENTS AND RESULTS
In general, modelling such a system involves developing a mathematical model,
programming and simulating the system on a computer. Next, we will simulate
the system's operation and model the city's socio-economic infrastructure.
First of all, the objects to be modelled, the city's socio-economic infrastruc-
ture and its components, are identified. In this case, these may include city zones,
residential and business units, enterprises and people, and CO2 emissions.
Intelligent information system of the city's socio-economic infrastructure
Системні дослідження та інформаційні технології, 2023, № 3 113
Next, it is necessary to investigate how these objects will interact with each
other, which is described using various algorithms and formulas. In this case, an
agent-based model was created, where each agent has its own set of characteris-
tics and interacts with other agents and the external environment.
Thus, the system uses an agent-based transport and dynamic model to simu-
late the movement of people and businesses in the city and their interaction. Each
agent (person or enterprise) has its own properties and can change its state
according to the interaction with other agents and changes in the environment.
For example, a person can change his or her job, move to another area, or buy a
car if he or she has sufficient funds. An enterprise can change its operation or
production in response to changes in demand for its products or services.
Data is collected automatically in real time. Traffic information is collected
using sensors on roads and vehicles and transmitted to the system for further proc-
essing and analysis. CO2 emissions are also collected and accounted for in the
system. In addition, the system analyses data on the level of comfort of housing,
the number of residential and commercial units in each zone, and other factors
that affect the standard of living in the city.
Modelling based on data from a specific city, such as Ternopil, is an impor-
tant stage in the development of an information system for managing socio-
economic infrastructure. It allows to take into account specific features of the city,
such as demographic, economic, transport and other characteristics.
Ternopil is a medium-sized city located in the western part of Ukraine. It has
a rich history, as well as important economic and cultural significance for the re-
gion and the country as a whole. According to the Ukrainian State Statistics
Committee, as of 1 January 2022, the population of Ternopil was over 219 thou-
sand people [15]. The age group selected for modelling is 25-54 years, which is
44% of all citizens [14], as this category belongs to the active working age group,
people who are potentially able-bodied citizens. This is an important factor for
modelling the city's socio-economic infrastructure, as this category of citizens are
the main users of transport and other public services, and the functioning of the
city's infrastructure depends on their activity.
Based on the Ternopil city model, we will highlight some properties that
may be characteristic of certain city zones:
1. The central area of Ternopil is the most commercial and business-oriented
zone, with a high level of comfort, but also with high property values.
2. The South-Western zone of the city is a residential zone with a low level
of comfort and average property prices.
3. The north-eastern area of the city is more industrial with a large number
of factories and plants, and few residential areas.
4. The area on the western edge of the city is a residential area with a high
level of comfort and high property prices.
5. The southern edge of the city is a more industrial area with few residential
areas and average property prices.
Based on expert data (Table), the values of the system input parameters were
formed.
An information system has been developed based on the model [15] and
adapted for the city of Ternopil.
Khrystyna Lipianina-Honcharenko, Yevgeniy Bodyanskiy, Anatoliy Sachenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 3 114
According to the results of the modelling carried out for a period of 1460
days, it was found that the largest number of enterprises (Fig. 3) is concentrated in
the central, western and southern zones of the city. This is due to the fact that
these zones are more developed in terms of economy and the location of the city
centre. The largest concentration of population (Fig. 3) is also observed in the
central and western zones of the city.
System parameters for the zones of Ternopil city
Zone Housing
capacity
Comfort
level
Number of places
for enterprises
Road capacity,
% of total traffic
Central 600 1 35 20
North-western zone 500 0.7 25 55
North-eastern 1000 0.5 100 85
Western 700 0.9 20 30
South 500 0.6 70 90
The modelling results showed
that the highest road congestion
(Fig. 4) in Ternopil is observed on
the route from the western zone of
the city to the north-eastern zone
through the city center. This is be-
cause most of the city’s residents
live in the western and central
parts of the city, but work in other
parts of the city, particularly in the
northeastern part. Thus, this route
is key for transporting people and
goods in the city.
The following is a more de-
tailed analysis of the indicators for
each zone.
First, the state of enterprises
Fig. 3. Modelling results: a — workload of enterprises; b — po
a b
Fig. 4. Road load
Intelligent information system of the city's socio-economic infrastructure
Системні дослідження та інформаційні технології, 2023, № 3 115
will be analyzed: the data is presented as a time series of three variables for each
point in time: growing, stable and unstable. Next, the data on the state of people,
this data is a survey where people are asked to assess their condition in relation to
their place of residence: satisfactory, acceptable or poor. And lastly, we will ana-
lyze the rate of moving from the respective area of the city to another.
So, let’s first look at the central zone indicator (Fig. 5). The state of enter-
prises is characterized by “growth” at the level of 50%. This may mean that the
overall level of economic development in the region is positive, or that there is a
certain level of stability in this area. The state of people in a “satisfactory” condi-
tion is 70%. This indicates that the majority of the population feels satisfied with
their lives, possibly due to economic achievements that allow people to meet their
needs. People most often move to the north-eastern zone. This may be due to cer-
tain factors, such as job opportunities, infrastructure development, better living
conditions or other factors.
According to the data, the state of enterprises in the Northwest zone (Fig. 6)
is stable on average with a business growth rate of 50%, but there is a certain
probability that the state will become “unstable”. The situation of people in this
zone is generally satisfactory with a comfort level of 70%. People tend to move to
the Western zone, probably because of the higher levels of comfort in this zone.
Therefore, the North-Western zone can be an attractive place to live and develop
business, provided that the businesses remain stable.
The North-Eastern zone is characterized (Fig. 7) by a less stable state of en-
terprises compared to other zones. The growth rate is less than 30%, although
sometimes it can become unstable and reach 50%. In such periods, enterprises
may have problems with maintaining and developing their business. The state of
people in this zone is relatively satisfactory, as most people are currently satisfied
with their situation. This may be due to the high level of employment in the area,
or possibly other social factors that keep people comfortable. Nevertheless, peo-
ple in the northeastern zone are more likely to move to the western zone, where
a b c
Fig. 5. Central zone: a — the state of enterprises; b — human condition; c — people
move to other zones every month
Fig. 6. North-Western zone: a — the state of enterprises; b — human condition; c — people
move to other zones every month
Khrystyna Lipianina-Honcharenko, Yevgeniy Bodyanskiy, Anatoliy Sachenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 3 116
they have a higher level of comfort. This may be due to fewer career opportunities
in the northeastern zone, or to a lower quality of life due to less stable businesses.
It is also possible that people are moving to the central zone, where there are more
employment and career opportunities.
The Western zone is characterized (Fig. 8) by a lower level of economic
growth compared to other zones. Most of the enterprises in the zone are in an
“unstable” state, which can create difficulties for businesses and investors. How-
ever, in most cases, the condition of enterprises is “stable”. People’s perception of
the area’s quality of life is fairly high, with a “satisfactory” rating of 85%. People
tend to move to the north-western zone, where housing is cheaper, and to the cen-
tral zone, where there is a higher level of comfort and opportunities for career and
business development.
In the Southern zone (Fig. 9), the situation of enterprises can be character-
ized as stable in most cases, although some enterprises may experience instability.
In general, the state of enterprises in this zone can be described as “growing” at
the level of 25–30%. As for the state of people, they are in a “satisfactory” state at
85%. People are most often moving to the central zone, as it offers a higher level
of comfort.
a b d
Fig. 9. Southern zone: a — the state of enterprises; b — human condition; c — people
move to other zones every month
Fig. 7. North-eastern zone: a — the state of enterprises; b — human condition; c — people
move to other zones every month
a b d
a b d
Fig. 8. Western zone: a — the state of enterprises; b — human condition; c —people
move to other zones every month
Intelligent information system of the city's socio-economic infrastructure
Системні дослідження та інформаційні технології, 2023, № 3 117
Also, the system has statistics (Fig. 10) that show that the total distance of
car trips has increased by 249% or more than three times (the initial distance was
83.661 km and now it is 208.414 km). This has also resulted in an increase in CO2
emissions by the same amount – 249% of the initial emissions level. This is an
indicator of increasing air pollution and can have a negative impact on human
health and the environment. This data can be used to evaluate the effectiveness of
programmers and policies aimed at reducing car traffic and air pollution.
It is also possible to display information on each individual enterprise
(Fig. 11) and person (Fig. 12).
Fig. 10. Statistics on CO2 emissions from motor vehicles
Fig. 12. Displaying information on people
Fig. 11. Display of information on the enterprise
Khrystyna Lipianina-Honcharenko, Yevgeniy Bodyanskiy, Anatoliy Sachenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 3 118
For example, the first 64 enterprises have 120 employees and a total monthly
production capacity of 57.5 thousand euros. The state of the enterprise is “grow-
ing”, which may indicate a successful team and effective business management.
The second enterprise 43 has a larger number of employees – 150 people. The
total monthly production capacity of this enterprise is 69.5 thousand euros. The
company’s condition is “stable”, which may indicate its long-term sustainability
and reliability. Overall, both enterprises have significant potential and can be suc-
cessful in the market for their respective goods and services. However, their fu-
ture development depends on how efficiently they use their resources and how
well they can adapt to changes in the current business environment.
The first person, 917 (Fig. 12), is 24 years old, lives in the north-western
zone and also works in the central zone. According to the status, she also consid-
ers her condition to be satisfactory, with an income of €1058 per month. The sec-
ond person 381 is 39 years old, lives in the southern zone and works in the central
zone. According to the status, she considers her situation to be satisfactory. Her
income is 892 euros per month.
Thus, during the 1460 days of modelling the socioeconomic infrastructure of
Ternopil, it was found that the state of enterprises in different zones has different
levels of growth, and the state of people is mostly satisfactory. People tend to
move to areas with higher levels of comfort or cheaper housing. The total distance
of car journeys has increased by 249%, resulting in CO2 emissions in line with
this increase. The model also provides information about two people – one living
in the southern zone and the other in the north-western zone, both working in the
center and in good health.
CONCLUSIONS
The concept of an intelligent information system for the provision of the city’s
socioeconomic infrastructure and the structure of the data flow in it have been
developed. This system will automate the distribution of powers between the state
and regional governments in the development of master plans for the development
of cities in the country, social programmers and other documents aimed at im-
proving the quality of life of the population.
Experimental results of the 1460-day simulation of the intelligent informa-
tion system for the city’s socioeconomic infrastructure show a 50% increase in
businesses in the central zone and a 70% increase in people’s satisfaction, as well
as a move of residents to the north-eastern and western zones due to a higher level
of comfort. The total distance of car journeys increased by 249%, and the change
in CO2 emissions also increased by the same percentage, which is negative for the
environment. The condition of enterprises in other zones is less stable, with lower
“growth” scores, but there are also zones with a stable and “satisfactory” con-
dition.
Further research may include the development of new methods and algo-
rithms for using data from the city’s socioeconomic infrastructure in intelligent
information systems, analysis of the impact of intelligent information systems on
the economic and social development of the city, development of new informa-
tion technologies for creating intelligent information systems, and research on the
impact of an intelligent information system on the environmental sustainability of
Intelligent information system of the city's socio-economic infrastructure
Системні дослідження та інформаційні технології, 2023, № 3 119
the city. In addition, the interaction of intelligent information systems with local
governments, business and the public, as well as the impact of intelligent informa-
tion systems on ensuring accessibility and equality of use of the city’s socioeco-
nomic infrastructure for all its residents and visitors can be studied.
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Khrystyna Lipianina-Honcharenko, Yevgeniy Bodyanskiy, Anatoliy Sachenko
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Received 15.03.2023
INFORMATION ON THE ARTICLE
Khrystyna V. Lipianina-Honcharenko, ORCID: 0000-0002-2441-6292, West
Ukrainian National University, Ukraine, e-mail: xrustya.com@gmail.com,
kh.lipianina@wunu.edu.ua
Yevgeniy V. Bodyanskiy, ORCID: 0000-0001-5418-2143, Kharkiv National University
of Radio Electronics, Ukraine, e-mail: yevgeniy.bodyanskiy@nure.ua
Anatoliy O. Sachenko, ORCID: 0000-0002-0907-3682, West Ukrainian National
University, Ukraine, e-mail: as@wunu.edu.ua
ІНТЕЛЕКТУАЛЬНО ІНФОРМАЦІЙНА СИСТЕМА СОЦІАЛЬНО-
ЕКОНОМІЧНОЇ ІНФРАСТРУКТУРИ МІСТА / Х.В. Ліп’яніна-Гончаренко,
Є.В. Бодянський, А.О. Саченко
Aнотація. Розвиток міст є важливою проблемою, яку можна вирішити за до-
помогою інтелектуальних інформаційних систем. Такі системи забезпечують
ефективне управління різноманітною інфраструктурою міста. Дослідники роз-
робили концепцію такої інформаційної системи, яка базується на концептуа-
льній моделі та використовує потік даних для розумного прийняття рішень.
Систему протестовано на період 1460 днів у місті Тернопіль. Результати моде-
лювання показали, що центральна зона міста є стабільною зі станом підпри-
ємств «зростаючий» на рівні 50% та станом людей у стані «задовільно» на рів-
ні 70%. Люди найчастіше переїжджають у північно-східну та західну зони
через вищий рівень комфорту та більш доступне житло, проте загальна від-
стань автомобільних поїздок збільшилась на 249%, що має негативний вплив
на довкілля. Стан підприємств у інших зонах є менш стабільним з нижчими
показниками «зростання», але є зони зі «стабільним» станом і станом «за-
довільно».
Ключові слова: моделювання, інформаційна система, соціально-економічна
інфраструктура, місто.
|
| id | journaliasakpiua-article-290412 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-07-17T10:28:22Z |
| publishDate | 2023 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
| record_format | ojs |
| resource_txt_mv | journaliasakpiua/11/b5fb3e2f46a08a731ac548d884c1b911.pdf |
| spelling | journaliasakpiua-article-2904122023-11-07T22:19:24Z Intelligent information system of the city's socio-economic infrastructure Інтелектуально інформаційна система соціально-економічної інфраструктури міста Lipianina-Honcharenko, Khrystyna Bodyanskiy, Yevgeniy Sachenko, Anatoliy modelling information system socioeconomic infrastructure city моделювання інформаційна система соціально-економічна інфраструктура місто Urban development is an important problem that can be solved with the help of intelligent information systems. Such systems ensure efficient management of the city’s diverse infrastructure. The researchers developed a concept of such an information system based on a conceptual model and using data flow for intelligent decision-making. The system was tested for 1460 days in the city of Ternopil. The modelling results showed that the city’s central area is stable, with 50% of enterprises in the “growing” state and 70% of people in the “satisfactory” state. People often move to the northeastern and western zones due to higher levels of comfort and more affordable housing. However, the total distance of car trips has increased by 249%, negatively impacting the environment. The condition of enterprises in other zones is less stable with lower “growth” indicators, but there are zones with “stable” and “satisfactory” conditions. Розвиток міст є важливою проблемою, яку можна вирішити за допомогою інтелектуальних інформаційних систем. Такі системи забезпечують ефективне управління різноманітною інфраструктурою міста. Дослідники розробили концепцію такої інформаційної системи, яка базується на концептуальній моделі та використовує потік даних для розумного прийняття рішень. Систему протестовано на період 1460 днів у місті Тернопіль. Результати моделювання показали, що центральна зона міста є стабільною зі станом підприємств "зростаючий" на рівні 50% та станом людей у стані "задовільно" на рівні 70%. Люди найчастіше переїжджають у північно-східну та західну зони через вищий рівень комфорту та більш доступне житло, проте загальна відстань автомобільних поїздок збільшилась на 249%, що має негативний вплив на довкілля. Стан підприємств у інших зонах є менш стабільним з нижчими показниками "зростання", але є зони зі "стабільним" станом і станом "задовільно". The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2023-09-29 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/290412 10.20535/SRIT.2308-8893.2023.3.08 System research and information technologies; No. 3 (2023); 108-120 Системные исследования и информационные технологии; № 3 (2023); 108-120 Системні дослідження та інформаційні технології; № 3 (2023); 108-120 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/290412/283982 |
| spellingShingle | моделювання інформаційна система соціально-економічна інфраструктура місто Lipianina-Honcharenko, Khrystyna Bodyanskiy, Yevgeniy Sachenko, Anatoliy Інтелектуально інформаційна система соціально-економічної інфраструктури міста |
| title | Інтелектуально інформаційна система соціально-економічної інфраструктури міста |
| title_alt | Intelligent information system of the city's socio-economic infrastructure |
| title_full | Інтелектуально інформаційна система соціально-економічної інфраструктури міста |
| title_fullStr | Інтелектуально інформаційна система соціально-економічної інфраструктури міста |
| title_full_unstemmed | Інтелектуально інформаційна система соціально-економічної інфраструктури міста |
| title_short | Інтелектуально інформаційна система соціально-економічної інфраструктури міста |
| title_sort | інтелектуально інформаційна система соціально-економічної інфраструктури міста |
| topic | моделювання інформаційна система соціально-економічна інфраструктура місто |
| topic_facet | modelling information system socioeconomic infrastructure city моделювання інформаційна система соціально-економічна інфраструктура місто |
| url | https://journal.iasa.kpi.ua/article/view/290412 |
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