Balkan Journal of Applied Mathematics and Informatics
GOCE DELCEV UNIVERSITY - STIP, FACULTY OF COMPUTER SCIENCE
SECURITY CHALLENGES AND SOLUTIONS IN ROBOTIC AND INTERNET OF ROBOTIC THINGS (IoRT) SYSTEMS: A SCOPING REVIEW
Robotic systems and the Internet of Robotic Things (IoRT) are rapidly expanding into domains such as healthcare, industry, logistics, and smart environments, bringing significant benefits but also exposing new security challenges. Because robots exchange data, interact with cloud and edge platforms, and operate autonomously, cyber incidents can cause information breaches and physical harm. This scoping review maps current research on IoRT security by analyzing studies published in the last five years. Using PRISMA methodology, the review identifies the main threats affecting IoRT systems-ranging from adversarial manipulation and data leakage to insecure wireless communication and vulnerabilities in learning-based components. The examined literature shows that most solutions focus on protecting data confidentiality, ensuring integrity of robotic behavior, and applying cryptographic or AI-driven defense mechanisms, while protocol-level security remains notably underexplored. Overall, the review reveals a growing yet fragmented field and highlights the need for more systematic evaluation of communication protocols and robust, trustworthy AI methods to secure increasingly autonomous robotic systems.
Copyright (c) 2025 Balkan Journal of Applied Mathematics and Informatics
A FHIR -CENTRIC APPROACH FOR INTEROPERABLE REMOTE PATIENT MONITORING
Interoperability of health information systems is one of the main challenges in modern clinical practice. Healthcare institutions often use different ICT solutions that do not communicate with each other, which leads to fragmented data, duplicate data, limited access to important patient information, and potential risks in making clinical decisions. The key problem lies in the absence of a universally adopted standard for the exchange of health information data. As a potential solution to this situation, the HL7 FHIR standard appears, developed to enable fast, easy, and secure exchange of health information, resulting in efficiency and consistency in patient care. This paper presents a practical implementation of the FHIR standard through the development of a specialized platform for blood pressure monitoring. The system architecture includes a mobile application intended for patients and a desktop-based application intended for doctors, which communicate via a RESTful API in accordance with the FHIR specification. The implementation demonstrates how the FHIR standard enables seamless interoperability, efficient exchange of structured data, and improved collaboration between patients and doctors, confirming its fundamental role in overcoming structural barriers in the context of modern e-health.
COMPARATIVE EVALUATION AND ANALYSIS OF DIFFERENT DEEPFAKE DETECTORS
Deepfakes, synthetic media generated using deep learning, pose significant risks to the integrity, security, and trust of information. Reliable detection is therefore critical, yet existing models often fail when exposed to realworld distortions such as compression, occlusion, and lighting variations. This paper presents a comparative evaluation of deepfake detection models, including XceptionNet, EfficientNet, MesoNet, and Vision Transformers, across multiple benchmark datasets such as FaceForensics++, DFDC, Celeb-DF, and Wild- Deepfake. Models are assessed not only under pristine conditions but also under controlled distortions that reflect realistic deployment environments. The results show that XceptionNet and the fine-tuned Vision Transformers achieve the strongest accuracy and robustness, maintaining competitive performance across domains, while MesoNet demonstrates computational efficiency but suffers from reduced reliability under challenging conditions. EfficientNet provides a balance between parameter efficiency and detection quality, but lags behind in cross-dataset generalization. The findings highlight clear trade-offs between robustness, efficiency, and deployment feasibility, emphasizing that lightweight models are best suited for edge scenarios, whereas more complex architectures remain preferable in cloud or high-resource environments. The study concludes with open challenges and future research directions, including the integration of multimodal cues, domain adaptation, and explainable detection frameworks, to improve resilience against increasingly sophisticated deepfake generation techniques.
Deepfake detection; Generative Adversarial Networks; Computer Vision; Robustness; XceptionNet; Vision Transformers; Benchmarking
METHODS OF EXTRACTION AND ANALYSIS OF PEOPLE'S SENTIMENTS FROM SOCIAL MEDIA
This study explores methods for extracting and analyzing people's sentiments from social media, utilizing advanced natural language processing and machine learning techniques. The goal is to recognize sentiments and based on them to categorize posts and comments as positive, negative, or neutral in order to understand users' attitudes and emotions. The algorithms used for sentiment classification in this research include Naive Bayes, SVM, Logistic Regression, and Random Forest. Additionally, the study analyzes and compares the performance of these algorithms in terms of accuracy, recall, and F1 score, providing a comprehensive overview of their effectiveness. It also emphasizes the importance of hyper-parameter tunning to improve the accuracy of classification algorithms. The results of this study can be used to assist social media platforms, researchers, and policymakers in developing strategies to manage and improve user experiences, as well as to make informed decisions based on user reactions.
SOLUTION OF DIDO’S PROBLEM USING VARIATIONS
Isoperimetric problems are an important class of variational problems. They represent problems in which the optimization is subject to one or more constraints. The term “isoperimetric problems” likely does not make you think of optimization with constraints. However, they have been given this name due to their origin, a problem from antiquity. Given a fixed perimeter, the problem asked to find the geometric figure that encloses the largest possible area. The answer is, perhaps intuitively, the circle. The techniques developed in this section show how to use calculus of variations to answer this and other similar questions. We begin by presenting a variant of this problem.
DESIGN AND SIMULATION OF A SCADA - CONTROLLED GREENHOUSE FOR OPTIMIZED ROSE CULTIVATION
This study presents the design and simulation of a SCADA system for monitoring and automated control of environmental and operational parameters in a rose greenhouse. Development of the SCADA system within this project was supported by the Ignition platform – a modern, modular and industrially oriented software solution from Inductive Automation, which enables the creation of SCADA, HMI and IoT applications. Careful design considerations were applied to ensure that the virtual model accurately reflects actual operational conditions. By modifying the parameters, the system can be easily adapted to manage different types of plants. The application of SCADA technology in horticulture enables advanced resource optimization strategies, resulting in enhanced greenhouse production outcomes, operational performance and efficiency. By combining design and simulation, this study highlights the potential of virtual SCADA systems as tools for planning, analysis, and development of efficient solutions for process management in contemporary horticulture. While the simulation confirms that the design meets all specified requirements, real greenhouse implementation would require modifications or adjustments to the control logic to adapt to actual operational conditions.
Tag, alarm, temperature, soil moist, air humidity, script
CNC LATHE PROGRAMMING: DESIGN AND DEVELOPMENT OF PROGRAM CODE FOR SIMULATING LINEAR INTERPOLATION MOTION
This paper builds upon the foundational work of simulating linear interpolation motion in CNC turning by advancing into the realm of CNC lathe programming. It focuses on the design and development of program code specifically tailored for simulating linear interpolation motion. By integrating G-code programming techniques with advanced simulation tools, this study provides a robust framework for visualising and analysing the precise motion paths in CNC lathe operations. The results contribute to improved accuracy and efficiency in CNC machining processes, offering valuable insights for both academic research and practical applications in the field of CNC programming.
Material removal, Metal cutting, Turning, G-codes, Program blocks
ADVANCED TOOLPATH VERIFICATION IN CNC DRILLING: APPLYING NEWTON’S INTERPOLATION THROUGH MATLAB
This paper presents an advanced methodology for toolpath verification in CNC drilling, utilising Newton's interpolation method along with Matlab. The primary objective is to develop a highly accurate model that precisely captures the dynamic behaviour of CNC drilling machines, allowing for meticulous control over the drill bit's trajectory. Newton's interpolation is crucial for accurately modelling the toolpath, which is essential for ensuring precision in drilling operations. Matlab is employed as the computational platform for implementing the interpolation method, enabling the generation of detailed visualisations of the CNC drilling process. This approach enhances drilling accuracy and efficiency, reduces tool wear, and effectively predicts the dynamic motion of the drill bit, offering significant benefits for both professionals and researchers in the field of precision machining.
Trajectory, Drill bit, CNC interpolator, Interpolating polynomial, Modelling
NEW RESULTS ON FIXED POINT THEOREMS IN 2-BANACH SPACES
In this article, we prove a common fixed point result for interpolative Kannan type contraction mappings in 2-Banach spaces. On the other hand, we introduce interpolative Dass and Gupta rational type contraction mappings on 2-Banach spaces. In particular, we discuss the existence of a fixed point of such a mapping in 2-Banach spaces.
Fixed point theorems, 2-Banach spaces, complete metric spaces.
MONITORING AND TRANSMISSION OF THE PROCESS PARAMETERS ON AGRO INDUSTRIAL FACILITY IN A GSM NETWORK
In modern technological and industrial development, the application of electronics in measuring, processing, storing and transferring process data in industrial facilities is increasing. In this processing of process parameters, it is essential that users have timely and accurate information about the measurement data in their industrial complex. Modern electronic systems provide the ability to process and store measurement data on-site and transfer it to the IoT and GSM network. On the other hand, the application of sophisticated electronic systems is noticeable not only in power plants, but also in healthy and quality food industries, such as agriculture. We witness daily tribunes and panel discussions sponsored by companies and even governments for the introduction of the terminology of digital agriculture, i.e. the introduction of smart electronic solutions in agriculture. In addition to the commitment to so-called green energy, i.e. obtaining energy from renewable sources, the development of digitization in agriculture is an area in which an enormous application of smart electronic systems is expected in the future. Guided by these reasons, in this paper an electronic system is designed that provides a solution to a problem in hydro melioration system, i.e. the development, design and practical implementation of the Smart electronic system which enables the measurement of the process parameters of an agro-industrial facility and their transfer to the GSM SIM network. The solution enables the visualization of process parameters locally on LCD displays and remotely on an mobile device in GSM SIM network. A data log file is also provided for store the value on the process parameters ​​on a local computer.
WEB-BASED EDUCATIONAL GAME FOR EARLY SCREENING AND SUPPORT DYSCALCULIA
Dyscalculia, a specific learning disorder affecting numerical and arithmetic processing, remains underdiagnosed due to the limited accessibility and engagement of traditional screening tools. This study presents the development and validation of a web-based educational game designed for the early screening and support of dyscalculia in children aged 9–12 years. Leveraging gamification and adaptive learning principles, the platform integrates psychometrically validated tasks within an interactive environment to assess core deficits in number sense, arithmetic fluency, and working memory. Experimental evaluation was conducted, with 16 participants (8 experimental, 8 control) undergoing pre- and post-test assessments using the standardized TEDI-MATH diagnostic tool. Results demonstrated statistically significant improvements in the experimental group (t(14) = 16.72, p < 0.001, Cohen's d = 8.36), indicating the game's effectiveness as both a screening instrument and intervention tool. These findings contribute to the growing body of research on digital learning technologies for special educational needs, offering a scalable solution that bridges the gap between early detection and intervention
ENHANCING GEOGRAPHIC INFORMATION SYSTEMS WITH SPATIAL DATA MINING
This paper explores how Geographic Information Systems (GIS) can be combined with Spatial Data Mining (SDM) to improve the understanding and utilization of large volumes of spatial data. The study begins by defining spatial data and highlighting its significance. It then examines the fundamental concepts of GIS and the methods for managing, analyzing, and modeling spatial data. Furthermore, the research identifies and explains the challenges that arise when integrating GIS with SDM, proposing possible solutions to overcome these issues. This paper provides a detailed insight into the synergy between GIS and SDM tools, aiming to enhance the management and analysis of large spatial data collections.
Geographic Information System, Spatial Data Mining, big data.
ANALYSIS OF THE MOVEMENT OF FLUCTUATIONS AND TRENDS OF THE GROSS DOMESTIC PRODUCT IN THE REPUBLIC OF NORTH MACEDONIA AND FORECASTS
In this paper, an analysis will be made of the movement of fluctuations and trends in the gross domestic product, in the period from 2000 to 2024 by quarter with current prices expressed in millions of denars in North Macedonia, using time series. The analysis will be done using the Python program. In the end, with the help of the previously prepared program and model, a prediction is made for the movement of trends and fluctuations in GDP in the period from 2024 to 2028.
STATE-OF-THE-ART COMPARISON OF MOBILESECURECOMM WITH MODERN SECURE COMMUNICATION PLATFORMS FOR TACTICAL OPERATIONS
Modern military and critical missions depend on secure, fast, and flexible communication systems that can perform reliably across various operational environments. Legacy platforms such as SINCGARS, EPLRS, and CERT-based emergency systems have offered foundational services, but they fall short when it comes to adapting to new threats, supporting modern data-intensive operations, or integrating with advanced technologies like artificial intelligence and quantum encryption. This paper presents a state-of-the-art comparison between existing secure communication platforms and a newly proposed system called MobileSecureComm. Designed for tactical operations, MobileSecureComm combines modular architecture, quantum-ready encryption, and AI-driven routing to meet the growing demands of modern warfare and emergency response scenarios. The paper draws from extensive literature covering secure mobile platforms, military-grade messaging systems, mobile edge computing, and real-world deployment models. Using simulation-based analysis, the study compares MobileSecureComm to 25 secure communication platforms in terms of latency, throughput, security, interoperability, and resilience. The results show that MobileSecureComm consistently achieves lower latency, higher data throughput, and stronger security safeguards than traditional platforms. It also offers seamless integration with NATO-compliant systems and the flexibility to scale across multi-domain operations. This paper highlights the importance of designing secure communication platforms that are not only technically advanced but also adaptable to changing threats and diverse mission requirements. MobileSecureComm provides a forward-looking solution that can help bridge the gap between existing systems and the future of tactical communication.
INTEGRATING AI AND CLOUD COMPUTING FOR EFFICIENT AUDIO ANALYSIS
Abstract. This paper propose a pipeline for sentiment analysis of audio inputs by using AI and techniques for speech recognition. A key aspect of our approach involves determining audio chunks based on silence detection and decibel height, allowing for more effective segmentation and analysis of the input data. These techniques will be instrumental in categorizing audio materials, enabling more organized and accessible content management. In the scope of this paper, we will compare and utilize several Python packages for audio detection, including Librosa, PyDub, and SoundFile, which offer various functionalities for audio analysis and manipulation. Additionally, we discuss the high computational demands associated with training and deploying of models, highlighting the potential cost barriers for many organizations. To address these challenges, we propose the use of cloud-based solutions, specifically AWS Spot Instances, Azure Spot VMs, and Google Cloud Preemptible VMs, which offer substantial cost savings for processing audio data. By leveraging these cloud resources, organizations can significantly reduce expenses while maintaining high performance in AI audio processing tasks.
AUTOMATED DOOR STATE DETECTION USING DEEP LEARNING: A COMPUTER VISION APPROACH WITH ROBOFLOW PLATFORM
This paper presents a deep learning-based approach for automated door state detection, capable of classifying doors as open, closed, or semi-open. The implementation leverages the Roboflow platform for comprehensive image processing and model development workflow. Our methodology encompasses data collection, annotation, augmentation, and model training using state-of-the-art deep learning architectures. The system demonstrates robust performance in real-world scenarios, offering potential applications in building automation, security systems, and smart home technologies. This work contributes to the growing field of automated building monitoring by providing a practical solution for door state recognition that can be integrated into existing surveillance and security infrastructures.
DEEP LEARNING-BASED DETECTION AND CLASSIFICATION OF DOCUMENT ELEMENTS USING ROBOFLOW
Recent advances in deep learning have enabled significant improvements in document understanding and processing. This paper presents a workflow for detecting and classifying key document elements—paragraphs of text, tables, signatures, and stamps—using deep learning models implemented through the Roboflow platform. We address the unique challenges of document element detection, including complex spatial relationships, overlapping boundaries, and varying formats across different document types. Our methodology leverages Roboflow's comprehensive toolkit for dataset preparation, model training, and deployment, with particular attention to data augmentation techniques specific to document processing. The proposed system achieves robust detection and classification of document elements. Experimental results demonstrate the system's effectiveness in real-world applications. Our findings indicate that the proposed approach offers significant accuracy and efficiency of automated document processing, particularly in scenarios requiring the precise identification and extraction of structured and unstructured document components.
MONITORING OF AC MOTOR SPEED CONTROLLER PARAMETERS TO IoT NETWORK
Today's development of electronics mainly takes place in two directions. One direction is based on the technological development of semiconductor elements that will work in a larger current, voltage and frequency range. The other direction is based on the development of information bases and systems that will ensure the collection, visualization, processing and transport of process parameters. The first direction will enable applications in power electronics for higher powers and process speeds, and the second local and remote transmission of process data and their availability in intranet and internet networks. Taking this into account in the paper, an electronic system is designed and implemented that measures, stores and transmits the parameters of a 1-phase AC motor speed controller in an IoT network. The solution enables the visualization of input and output parameters locally on two LCD displays and remotely on an IoT device. A data log file is also provided for the measured values ​​on a local computer and on an IoT cloud computer.
AC motor controller, Integrated circuit, Data log file, Blynk cloud
SMART CITY: A REVIEW OF CURRENT DEVELOPMENTS AND IMPLEMENTATION OF SMART GRID TECHNOLOGY
To ensure better living standards for the population, it is necessary to develop smart cities that utilize modern technology and operational efficiency to facilitate daily life. The primary goal of implementing (or creating) a smart city is to maintain, balance, and continuously upgrade economic, social, and environmental resources while managing costs. Emphasis is placed on maximizing the use of natural resources through energy conservation (utilizing renewables), efficient water usage, time savings, land optimization, environmental quality, traffic management, and the extensive use of information and communication technology systems and services for effective management and their ongoing enhancement. This work aims to create improved functionality, smart connections, and better organization among people, while maximizing the use of natural resources, minimizing environmental pollution, and improving public health.
technology, natural resources, upgrading, green energy
GENERALIZATION OF APPLICATION OF FUNDAMENTAL LEMMA OF VARIATIONAL CALCULUS
Variational calculus studied methods for finding maximum and minimum values of functional. It has its inception in 1696 year by Johan Bernoulli with its glorious problem for the brachistochrone: to find a curve, connecting two points A and B , which does not lie in a vertical, so that heavy point descending on this curve from position A to reach position in for at least time. In functional analysis variational calculus takes the same space, as well as theory of maxima and minimum intensity in the classic analysis. In this paper we will prove a theorem for functional where proves that necessary condition for extreme of functional is the variation of functional is equal to zero.
This paper presents a comparative analysis of prominent BPMN (Business Process Model and Notation) tools, including Camunda, Bizagi Modeler, bpmn.io, ProcessMaker, and Lucidchart. We evaluate these tools based on key criteria such as features, functionality, usability, integration capabilities and cost. By examining their strengths and limitations, we aim to provide a comprehensive overview that assists organizations in selecting the most suitable tool for their business process modelling needs. The analysis includes practical insights into each tool's effectiveness in facilitating process design, simulation and execution, offering valuable guidance for practitioners and decision-makers.
BPMN tools, Camunda, Bizagi Modeler, bpmn.io, ProcessMaker, Lucidchart.
Copyright (c) 2024 Balkan Journal of Applied Mathematics and Informatics
Business Process Model and Notation (BPMN) and Unified Modeling Language (UML) are two widely adopted tools for modeling in business and software engineering respectively. This paper explores the use cases for both BPMN and UML tools, highlighting their respective applications, differences, and synergies. By examining their features and specific scenarios where each tool excels, this research provides insights into how organizations can effectively leverage these tools for optimal outcomes.
BPMN tools, UML tools, Camunda, Bizagi Modeler, Lucidchart, StarUML, Enterprise Architect, Visual Paradigm, ArgoUML;
ON THE INTERGRABILITY OF A SUBCLASS OF 2D MATRIX DIFFERENTIAL EQUATIONS
In this paper, the 2D matrix differential equations are considered. Under certain conditions, using the Rodrigues’ formula for these 2D matrix differential equations, a particular solution is obtained. Finally, this theory is supported by examples.
2D matrix differential equations, Rodrigues’ formula, integrability
APPLICATION OF CENTER OF GRAVITY METHOD FOR LOCATIONS OF FACILITIES
The facility location decision is a critical aspect of operations management, with transportation costs often serving as a primary consideration. The Center of Gravity (COG) method has emerged as a practical tool for its simplicity in estimating optimal facility locations. This paper provides a comprehensive review of the COG method, acknowledging its strengths as a quick approximation tool but also highlighting its limitations. We delve into the method's assumptions, notably the uniformity of transportation costs, and discuss its application in dynamic and complex environments. Furthermore, we advocate for a holistic approach to facility location decisions, incorporating factors such as market competition, legal constraints, and environmental sustainability. To address these complexities, we propose the integration of advanced tools and techniques, including optimization algorithms, geographical information systems (GIS), and machine learning. By embracing a more sophisticated analytical framework, organizations can make informed decisions that align with broader business objectives, ensuring that facility locations are strategically chosen beyond the narrow focus on transportation costs. This paper aims to guide practitioners and researchers in navigating the intricacies of facility location planning, emphasizing the importance of a nuanced and advanced approach.
The science of digital forensics is an ever-changing and complex field which demands continuous advancements and development. It involves examining and extracting data from electronic devices which can consequently be used as digital evidence in the investigation of potential criminal activities. The forensic experts work tirelessly on finding new and improved tools which can make the research in the field more effective and the practical work of the examiners more productive. The processes and procedures are also constantly updated to follow the technological advances, in order to keep up with the trends lead by the manufacturers of electronic devices. The following research paper provides detailed description of the process of examination and extraction of data from mobile phones with android operating system. The detailed description explains the standardized procedures in stages, categorized in logical and chronological order to depict the work tasks of a digital forensic examiner. In addition to the theoretical explanation, this paper also offers practical examples of digital forensic examination. This practical examination was conducted to supports the key points of the elaborated research. Key words: digital forensics, mobile phone, android operating system
digital forensics, mobile phone, android operating system
POSSIBILITIES FOR INSTALLATION OF PHOTOVOLTAIC SYSTEMS IN CATERING FACILITIES IN MACEDONIA
The energy crisis that swept across Europe and the resulting electricity price impact have highlighted the need for enhanced energy resilience. To mitigate future price fluctuations and unforeseen shocks, investments in photovoltaic (PV) systems are crucial. Hospitality establishments in Macedonia hold significant potential for reducing the country’s energy dependency and accelerating the energy transition. It is therefore essential to explore the feasibility of installing PV systems on these establishments and to assess the profitability of such investments. For an optimal analysis of PV system installation potential in the hospitality sector, data from the State Statistical Office, based on the 2021 census in Macedonia, were utilized. According to the census, there are a total of 1,006 hotels and restaurants in the country. This analysis presents the total potential installed capacity of PV systems on all hotels and restaurants in Macedonia, the predicted annual electricity generation from these systems, and the resulting avoided CO2 emissions. Since the intensity of solar radiation varies geographically, simulations were conducted for PV systems with an installed capacity of 40 kWp in each region: Vardar, Eastern, Southwestern, Southeastern, Pelagonia, Polog, Northeastern, and Skopje regions. These simulations were performed using the PV*SOL premium software, which leverages the Meteonorm database for solar radiation data to estimate annual electricity production from the PV systems. The analysis also includes case studies for a hotel and a restaurant, for which techno-economic analyses were conducted to evaluate the profitability of PV system installations.
photovoltaic systems, installed capacity, electricity generation, techno-economic analyses.
MULTI-ACTION GRID AUTHENTICATION: A SECURE AND USABLE AUTHENTICATION SYSTEM FOR SMART TOUCH DEVICES
In the digital age, securing smart touch devices is of paramount importance to safeguard sensitive information. Traditional graphical password systems, while convenient, remain vulnerable to attacks such as shoulder surfing and smudge tracing. This paper introduces a novel multi-action grid authentication system that enhances security while preserving ease of use. The system allows users to authenticate by performing two actions—tapping and replacing—within a 3x3 grid. Through iterative development and testing, the method shows significant improvements in preventing common security threats while maintaining high user satisfaction. A thorough analysis of password space is also conducted, demonstrating the system's robust resistance to brute-force attacks. Our findings suggest that this multi-action approach offers a secure, efficient alternative to existing graphical password systems.
DETERMINATION OF ALGEBRAIC POINTS OF LOW DEGREE ON A FAMILY CURVES
Let n be a positive integer. The purpose of this paper is to determine explicitly algebraic points of low degree over Q on the family curves of affine equation y3n=x4n-1. An algebraic point of degree at most 2 is called an algebraic point of low degree. The essential tools for this determination are the theorem of Chevalley-Weil, cyclotomic polynomials, rational morphisms between these curves and the special Picard curve of affine equation y3=x4-1.
EXIBITION PRAMETRIC FAMILY OF ALGEBRIC POINTS OF GIVEN DEGREE ON THE AFFINE EQUATION CURVE: −y2 = x6 − 20x3 − 8
We give an explicit parametric family of algebraic points of given degree on Q over the affine equation curve: -y2 = x6 - 20x3 - 8. These curves are described by Nils BRUIN in [1], who showed that the MordellWeill group is finite and explained the generators of the torsion group for this curve.
AUTONOMOUS SOLUTIONS FOR DESIGN AND IMPLEMENTATION OF MODULAR STRUCTURES
Our objective with this paper is to analyze and explore emerging autonomous solutions for designing and implementing modular structures. Modular structures have been in use since the 1950s, so the concept is not new to us. Historically, the popularity of modular structures peaked following catastrophic natural disasters or wars, in areas that required rapid rebuilding. However, modular construction somewhat fell out of favor afterward. Nowadays, its popularity is resurging, becoming a notable trend once again. The robots employed in modular construction offer distinct advantages over those used in traditional construction, with streamlined tasks and enhanced efficiency. In this paper, we plan to analyze drones, loaders, cranes, and worker bots. These robots will serve various roles, including observation, construction, organization, and excavation. Furthermore, we aim to integrate these robots with cutting-edge technologies such as artificial intelligence, augmented and virtual reality, the internet of things, cloud services, and building information modeling - BIM.
Modular construction, Autonomous robots, Drones, Artificial intelligence, IoT