The American Journal of Management and Economics Innovations
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TYPE
Original Research
PAGE NO.
50-58
10.37547/tajmei/Volume07Issue04-06
OPEN ACCESS
SUBMITED
27 February 2025
ACCEPTED
24 March 2025
PUBLISHED
21 April 2025
VOLUME
Vol.07 Issue04 2025
CITATION
Jaspreet Kaur Lall. (2025). Use of BIM Technologies In Managing the
Refurbishment of Residential and Commercial Properties. The American
Journal of Management and Economics Innovations, 7(04), 50
–
58.
https://doi.org/10.37547/tajmei/Volume07Issue04-06
COPYRIGHT
© 2025 Original content from this work may be used under the terms
of the creative commons attributes 4.0 License.
Use of BIM Technologies
In Managing the
Refurbishment of
Residential and
Commercial Properties
Jaspreet Kaur Lall
Project Manager at Carter Jonas Birmingham, England
Abstract:
This article examines the potential of
building information modeling (BIM) technologies in
managing the reconstruction of residential and
commercial properties, with a focus on cultural
heritage preservation. The theoretical foundation
includes an analysis of BIM technologies, generative
design, and digital twins, as well as their integration
for precise digital modeling, optimization of design
solutions, and dynamic monitoring of operational
parameters. A case study of the reconstruction of the
former
Santa
Barbara
cinema
in
Paternò
demonstrates that the comprehensive application of
these technologies significantly enhances design
accuracy, improves energy efficiency, optimizes
operational performance, and preserves the historical
integrity of the structure. The findings confirm the
hypothesis that integrating BIM with modern digital
tools is an effective approach for managing
reconstruction
projects,
providing
substantial
practical value for professionals in architecture,
construction, and real estate management. The article
also presents recommendations for further research
aimed at improving generative design algorithms and
enhancing the reliability of digital twins. The topic of
BIM technology application in reconstruction
management will be of interest to leading specialists
in architectural and engineering design, strategic
construction project management, and urban studies,
as it offers an innovative methodological framework
for integrating digital tools to optimize reconstruction
processes, minimize technological risks, and ensure
the sustainability of urban infrastructure.
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Keywords:
BIM, generative design, digital twin, building
reconstruction,
cultural
heritage
preservation,
automation, IoT, energy efficiency.
Introduction:
The reconstruction of residential and
commercial properties is one of the key challenges in
the modern construction industry, driven by the need
to enhance energy efficiency, ensure urban
sustainability,
and
preserve
cultural
heritage.
Traditional methods of design and reconstruction
management often fail to account for the complex
interplay of factors such as structural integrity,
operational performance, and historical value. In this
context, the adoption of digital technologies has
become essential. Building Information Modeling (BIM)
plays a particularly significant role, as it enables the
creation of comprehensive digital models throughout
the entire lifecycle of a building, significantly improving
the accuracy of design solutions and enhancing
coordination
among
all
project
participants.
Additionally, modern generative design methodologies
and the use of digital twins, combined with Internet of
Things (IoT) systems, open new possibilities for dynamic
monitoring and management of reconstructed
buildings.
Azhar S. and Brown J.
[2] highlight BIM’s potential as a
tool
for
conducting
detailed
environmental
assessments and optimizing building lifecycles. The
study by Cascone S., Parisi G., and Caponetto R. [1] also
presents an example of BIM application in the design of
the Santa Barbara cinema. Similarly, Pereira V. et al. [6]
conduct a systematic and scientometric analysis of BIM
implementation for improving energy efficiency,
emphasizing the need for an integrated approach to
incorporating digital tools into the management of
building performance.
Furthermore, Ajtayné Károlyfi K. and Szép J. [3] propose
a parametric BIM framework for conceptual structural
design aimed at evaluating embodied environmental
impact, addressing an existing research gap in early-
stage design with a focus on sustainability metrics.
Liberotti R. and Gusella V. [4] demonstrate how
parametric modeling can be integrated into design
processes to support sustainable restoration of historic
buildings. Meanwhile, Gigliarelli E., Calcerano F., and
Cessari L. [5] combine heritage BIM, numerical
modeling, and decision-support systems to optimize
renovation processes. However, their research often
lacks a comprehensive approach to reconstruction
management
during
project
implementation,
highlighting a gap in the integration of theoretical
models with practical solutions.
Sun Y. and Dogan T. [7] propose generative methods for
rapidly exploring solution spaces in urban design,
significantly accelerating the development of optimal
urban planning concepts. Similarly, Qian C., Tan R. K.,
and Ye W. [8] employ adaptive algorithms based on
artificial neural networks for generative layout design,
while Ghannad P. and Lee Y. C. [9] present an
automated approach to modular residential design
using configuration algorithms and generative
adversarial
networks
(CoGAN).
These
studies
emphasize the drive toward automation and
adaptability in design solutions; however, they often do
not account for the specific requirements of
reconstructing buildings with historical or cultural
significance.
Summarizing the analysis, the identified research gap
lies in the insufficient integration of BIM technologies
with modern generative methods and artificial
intelligence
algorithms
for
comprehensive
reconstruction management. Such integration should
simultaneously meet the requirements of energy
efficiency, sustainable development, and cultural
heritage preservation.
The objective of this study is to analyze the potential of
BIM technologies in managing the reconstruction of
residential and commercial properties. This includes
the integration of generative design and digital twins to
enhance the accuracy of design solutions, improve
operational performance, and ensure compliance with
modern energy efficiency and sustainability standards.
The study’s sc
ientific novelty is determined by the
synthesis of research perspectives on BIM technologies
with generative design methods and environmental
assessments.
The
research
hypothesis
suggests
that
the
implementation of BIM technologies combined with
generative design methods and digital twins
significantly improves the building reconstruction
process. This improvement is reflected in enhanced
modeling accuracy, optimized engineering solutions,
reduced energy consumption, improved user comfort,
and the preservation of the cultural identity of historic
structures.
The methodological framework of this study is based on
a comparative analysis of scientific articles by other
researchers.
Theoretical framework: BIM, generative design, and
digital twins in building reconstruction
In modern conditions, the reconstruction of both
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The American Journal of Management and Economics Innovations
residential and commercial buildings requires a
comprehensive approach that not only restores the
physical structure but also ensures high energy
efficiency, optimizes operational performance, and
preserves cultural heritage. In this context, the
application of digital technologies has become an
integral part of management processes. This section
provides a theoretical foundation for three key areas:
Building Information Modeling (BIM), generative
design, and digital twins, which enable the integration
of
these
approaches
into
comprehensive
reconstruction management.
Building Information Modeling (BIM) is the process of
creating and managing a digital representation of a
building’s physical and fu
nctional characteristics
throughout its entire lifecycle. The use of BIM enables
the development of detailed parametric models that
integrate architectural, structural, and engineering
data, significantly improving design accuracy and
interdisciplinary collaboration. The main advantages of
BIM include:
●
Creation of a unified information model:
Consolidating data from various specialists (architects,
engineers, contractors) within a single digital
environment helps minimize errors and improve the
quality of the final project.
●
Parametric modeling: The ability to dynamically
adjust model parameters allows for rapid responses to
changes in project requirements and reconstruction
conditions.
●
Compliance with standards and data exchange:
The use of IFC formats and relevant standards (such as
UNI 11337) ensures compatibility and transparency in
project documentation.
Generative design relies on algorithmic methods and
computational models to automate the creation of
multiple design options based on predefined
parameters and constraints. This method enables
iterative modeling, which is particularly important in
the reconstruction of historically significant buildings,
where both structural constraints and aesthetic
considerations must be taken into account [8]. The key
capabilities of generative design include:
●
Iterative
analysis
of
design
solutions:
Automatic generation and evaluation of multiple
options allow for the selection of the most optimal
solution based on spatial efficiency, structural stability,
and energy performance.
●
Parameter optimization: Algorithms can
consider numerous variables, ensuring the adaptation
of the model to the specific requirements of
reconstruction.
●
Reduction of development time: Automation
significantly reduces the time required compared to
traditional manual design methods.
A digital twin is a virtual representation of a physical
object that synchronizes with the real state of a building
through data collected from Internet of Things (IoT)
sensors. This technology enables real-time monitoring
of operational performance, failure prediction, and
optimization of engineering system functionality [7, 8].
The comprehensive application of these technologies
creates a synergistic effect, improving the quality of
reconstruction projects by integrating the precision of
digital modeling, the flexibility of algorithmic solutions,
and real-time monitoring of operational parameters.
The integration of BIM with generative design
facilitates the creation of optimized design solutions,
which can then be dynamically adjusted based on data
received through the digital twin [2, 5].
For a clearer understanding of the key characteristics
and interrelation of these technologies, the table below
is presented.
Table 1. Comparative characteristics of BIM, generative design, and digital twins (compiled by the author
based on the analysis of the source [1]).
Technology
Key Capabilities
Advantages
Limitations
BIM
• Creation of detailed digital
models
• Integration of architectural,
structural, and engineering
data
• Support for parametric
modeling
•
Improved
design
accuracy
•
Enhanced
interdisciplinary
collaboration
• Reduction of errors
and project execution
•
High
qualification
requirements
for
specialists
• Dependency on specific
software
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time
Generative
Design
• Automated generation of
multiple design variants
•
Iterative
optimization
based on predefined criteria
(spatial efficiency, structural
stability, etc.)
• Rapid creation and
evaluation of design
solutions
•
Flexible
model
adaptation
• Reduced development
time
• Requires significant
computational resources
• Complexity in setting up
algorithms
and
parameters when multiple
constraints exist
Digital
Twins
• Virtual representation of an
object synchronized with
real-world conditions
• Real-time monitoring of
operational performance
•
Predictive
maintenance and failure
prevention
• Dynamic management
of engineering systems
•
Improved
user
comfort
• Dependence on the
accuracy and stability of
IoT sensors
• Need for a reliable
connection to information
systems
The combined use of these technologies enables
detailed digital modeling, flexible optimization of
design solutions, and dynamic monitoring of
operational parameters, which is particularly important
for projects involving historically and culturally
significant buildings. This approach lays the foundation
for creating sustainable, energy-efficient, and
functional reconstructed spaces that meet modern
standards in construction and real estate management.
Methodological
approach
to
reconstruction
management using BIM technologies
The methodology for implementing reconstruction
projects using BIM technologies includes the following
key stages:
●
BIM modeling. At the initial stage, an
integrated digital model of the building is created,
encompassing
architectural,
structural,
and
engineering systems. The use of specialized software
(such as Autodesk Revit) enables the development of
parametric families, ensuring dynamic updates to the
model when design changes are made. The application
of data exchange standards (such as the IFC format) and
national requirements (e.g., UNI 11337) guarantees
high accuracy and interoperability of the model among
different project stakeholders [6, 9].
●
Implementation of generative design. The
creation of multiple alternative design solutions is
carried out using visual programming algorithms (such
as Dynamo). This stage allows for the automatic
generation and evaluation of various options based on
predefined criteria, including spatial efficiency,
structural
stability,
and
energy
performance.
Generative design significantly accelerates the
optimization process and reduces the time required
compared to traditional manual design methods.
●
Integration of monitoring and management
systems. The next stage involves the deployment of
monitoring and control systems based on data received
from Internet of Things (IoT) sensors, as well as the use
of digital twins. Real-time data is integrated into the
BIM model, allowing for automatic adjustments to
engineering
systems
(heating,
ventilation,
air
conditioning, lighting, and shading) and facilitating
preventive maintenance. This approach contributes to
reduced energy consumption, improved user comfort,
and the timely resolution of system failures.
●
Use of a common digital platform (CDE). To
ensure efficient information exchange between
architects, engineers, contractors, and clients, a unified
digital platform is implemented. This enables real-time
updates to project documentation, minimizes errors,
and facilitates the coordination of design changes,
which is particularly crucial for the reconstruction of
historically significant buildings [1, 8].
For a more in-depth understanding of the interrelations
between the stages of this methodology, Table 2 is
presented below.
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Table 2. The stages of the methodological approach to reconstruction management using BIM technologies
Compiled by the author based on the analysis of the source [1].
Stage
Description
Tools/Technologie
s
Advantages
Limitations
BIM
Modeling
Creation of a detailed,
integrated digital model
of the object, including
architectural, structural,
and
engineering
components
Autodesk
Revit,
IFC
formats,
parametric families
High modeling
accuracy, real-
time
data
updates,
compliance
with
international
standards
Requires
specialized
skills,
significant time
and
financial
investment for
software
implementation
Generative
Design
Iterative creation of
multiple design options
based
on
visual
programming
algorithms, optimized
according to predefined
criteria
Dynamo,
optimization
algorithms,
computational
platforms
Rapid
generation
of
alternative
solutions,
adaptive
optimization,
reduced
development
time
High
computational
resource
requirements,
need for precise
algorithm
configuration
Integration of
Automated
Management
Systems
Implementation
of
monitoring
and
management
systems
using IoT and digital
twins integrated into
the BIM model
IoT sensors, digital
twins, automation
scenarios (based on
Dynamo)
Real-time
monitoring
of
operational
parameters,
reduced energy
consumption,
preventive
maintenance
Dependence on
data
quality,
integration
complexities
with
existing
systems
Coordination
and
Collaboration
Organization of joint
work among all project
participants through a
unified digital platform,
real-time information
exchange
CDE
platforms,
cloud
services,
project
management
systems
Improved
communication,
reduced errors,
faster decision-
making
Challenges in
standardization
alignment,
need
for
continuous
interaction
among
participants
The comprehensive integration of these stages enables
the creation of a flexible and adaptive reconstruction
management system. The developed BIM model serves
as a foundation for subsequent generative design,
where iterative optimization produces solutions that
meet the functional and energy requirements of
reconstruction. The implementation of automated
management systems integrated with digital twins
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ensures continuous monitoring of the building’s
operational characteristics and allows for prompt
responses to changes in external and internal
conditions. Overall, coordination and information
exchange among project participants contribute to risk
reduction, lower time and financial costs, and improved
quality in reconstruction projects.
Case study: application of BIM technologies in
reconstruction using a specific object
This section provides a detailed analysis of the
application of BIM technologies in the reconstruction
process of a specific site
—
the former Santa Barbara
cinema in Paternò. This building, possessing significant
historical and cultural value, serves as a unique
example of combining heritage preservation with the
implementation of modern digital technologies to
optimize design solutions and improve the operational
characteristics of the reconstructed structure.
The former Santa Barbara cinema was established in
the early 20th century and for many years served as a
cultural hub for the city, hosting film screenings,
theatrical performances, and public events. Over time,
due to changing socio-economic conditions and the
emergence of alternative entertainment formats, the
building fell into decline, leading to the deterioration of
its
architectural
appearance
and
functional
characteristics.
The primary objective of the cinema's reconstruction is
to preserve the building’s historical identity while
modernizing its engineering systems and enhancing
operational performance. To achieve this goal, the
project defined the following key tasks:
●
Preservation
of
historical
appearance.
Restoration and conservation of original architectural
elements to maintain the cultural identity of the
structure.
●
Structural reinforcement. Implementation of
repair work aimed at restoring load-bearing elements
and eliminating structural defects.
●
Modernization
of
engineering
systems.
Replacement of outdated heating, ventilation, air
conditioning, electrical, and plumbing systems with the
integration of energy-efficient technologies.
●
Integration
of
automated
management
systems. Deployment of a digital twin and IoT sensors
to enable real-time monitoring and management of
operational parameters [1, 6].
During the design phase, a detailed BIM model of the
building was created using Autodesk Revit,
incorporating architectural, structural, and engineering
data. The use of parametric modeling allowed for the
consideration of historical construction features and
the preservation of original elements while integrating
modern engineering solutions (Fig. 1).
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Fig. 1. Current state of the “Ex Cinema Santa Barbara” derived from the BIM model [1]
The iterative process of creating alternative options
made it possible to evaluate design solutions based on
criteria such as structural stability, energy efficiency,
and compliance with aesthetic requirements, ensuring
an optimal balance between preserving historical
appearance and meeting modern functional needs [4,
5].
One of the key stages of the project was the
implementation of automated management systems
based on the integration of digital twins and IoT sensors
[1, 3].
For a deeper understanding of the project's
implementation stages, Table 3 presents the main
activities, applied technologies, and achieved results.
Table 3. The main stages and results of the reconstruction of the former cinema "Santa Barbara" Compiled by
the author based on the analysis of the source [1].
Project
Stage
Main Activities
Applied
Technologies
Key Results
Historical
Assessment
and
Diagnostics
Comprehensive diagnostics, including
laser scanning, non-destructive testing,
evaluation of structural and engineering
system conditions, and analysis of
historical element preservation
Laser
scanning,
HBIM
Identification
of
structural
defects,
façade damage, and
engineering
system
deterioration, defining
restoration directions
BIM
Creation of a detailed BIM model of the Autodesk
Development of an
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Modeling
building, incorporating architectural,
structural, and engineering components,
using parametric families and data
exchange standards (IFC)
Revit,
IFC,
parametric
families
accurate digital model
providing a foundation
for design optimization
and
project
coordination
Generative
Design
Automated generation of alternative
reconstruction solutions based on
energy efficiency, structural stability,
and historical preservation criteria
Dynamo,
optimization
algorithms
Identification
of
optimal
design
solutions that maintain
historical
integrity
while
incorporating
modern
engineering
systems
Integration
of
Automated
Systems
Implementation of IoT sensors and a
digital
twin
for monitoring and
managing HVAC, lighting, and shading
systems; development of automation
scenarios for parameter adjustments
IoT,
digital
twin,
automation
scenarios
(Dynamo)
Real-time monitoring,
reduced
energy
consumption,
and
enhanced user comfort
Coordination
and Project
Execution
Establishment of a unified digital
platform for data exchange among
project participants, real-time updates of
the BIM model, and coordination of
design changes
CDE
platforms,
cloud
services
Improved
communication,
reduced errors, and
timely decision-making
The implementation of the reconstruction project for
the former Santa Barbara cinema demonstrated the
high efficiency of applying BIM technologies in
managing the restoration of historically significant
structures. The key achievements of the project
include:
●
Increased accuracy of design solutions. The
developed BIM model enabled a detailed analysis of the
building's structural and engineering features,
minimizing
errors
and
facilitating
real-time
modifications.
●
Optimization of engineering systems. Iterative
generative design contributed to selecting optimal
solutions that balanced modern energy efficiency
requirements with the preservation of the building’s
historical appearance.
●
Dynamic
management
of
operational
parameters. The integration of digital twins and IoT
sensors allowed real-time monitoring, automated
control of engineering systems, and reduced energy
consumption, improving overall user comfort.
●
Improved interdisciplinary collaboration. A
unified digital platform for project coordination
ensured timely information exchange, significantly
reducing risks and project implementation time.
This case serves as a clear example of successfully
combining cultural heritage preservation with the
adoption of modern engineering solutions, providing
significant practical value for future reconstruction
initiatives.
CONCLUSION
The application of BIM technologies, complemented by
generative design methods and the integration of
digital twins, enables the development of an efficient
building reconstruction management system that
meets modern energy efficiency requirements while
preserving cultural heritage. The case study of the
reconstruction of the former Santa Barbara cinema in
Paternò demonstrated that creating a detailed BIM
model, automatically generating optimal design
solutions, and implementing real-time monitoring
systems significantly enhance the accuracy of design
decisions and the operational performance of the
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building.
The results confirm the proposed hypothesis that the
comprehensive
application
of
modern
digital
technologies serves as a powerful tool for managing
reconstruction projects, contributing not only to the
optimization of engineering solutions but also to the
preservation of the historical identity of buildings. This
study provides practical recommendations for
professionals in architecture and construction, as well
as outlines promising directions for further research.
These include the advancement of generative design
algorithms, improving the reliability of digital twins,
and integrating artificial intelligence methods for
predicting the operational characteristics of buildings.
This research contributes to the development of digital
technologies in the construction industry and confirms
their significance for the comprehensive reconstruction
of buildings while preserving cultural heritage.
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