Construction Entities Research Articles

Three-dimensional Change Detection and Description in Complex Construction Scenarios

Abstract. In large-scale engineering construction scenarios, construction objects and equipment are numerous; their spatial positions and postures change frequently and are complex and varied. Describing the changes between construction entities and the entities themselves in a three-dimensional (3D) geometric space and functional semantic space is challenging. In response to this challenging, we propose a novel workflow to detect and describe the changes in a construction site. First, we add the constraint of object surface continuity to the octree change detection (OCD), exclude the independently changing cells, and improve the change detection robustness. Second, based on the changes in entity elements that occur in the 3D geometric space, we introduce six-type semantics to characterize the changes that occur. Differing from existing change detection semantic description methods that focus on the attribute semantics of changed entity elements, our method focuses on the semantic description of the change process. Finally, for the variations in different semantic types, we propose specific quantization methods that can better quantify the variations in entity elements in 3D geometric space. For the proposed solution, we tested it using two sets of multi-period time-series point cloud data, which can accurately identify the changing construction entities in space and complete the calculation of bridge construction progress, including the building demolition and construction, and the change in the construction apparatus position.

MCKP: Multi-aspect contextual knowledge-enhanced prompting for conversational recommender systems

Empowering conversational recommender systems (CRSs) with knowledge facilitates the generation of high-quality human-like recommendation proposals to users. Despite substantial endeavors in developing knowledge-based CRSs, they mainly focus on modeling entity knowledge by introducing external data, which cannot sufficiently contribute to understanding complex contextual semantics. Additionally, the source of knowledge relies on external data, ignoring the effective use of original training data, significantly increasing the cost of building efficient CRSs.To tackle the issues above, we explore how to leverage raw dialogue data for modeling and exploiting contextual knowledge to compensate for existing knowledge's shortcomings. Specifically, we first train knowledge generators by constructing multiple standard hybrid prompt templates and answer spaces, which is conducive to perceiving the reasons behind contextual connections from multiple aspects and storing corresponding contextual knowledge. Then, we design answer-guided prompt templates based on the answer space, closing the gap between inference and training of knowledge generators and facilitating the generation of aspect-specific contextual knowledge. Next, we extend our approach by harnessing external knowledge graphs to construct entity knowledge. We propose a local-to-global semantic fusion strategy to fuse knowledge representations from different sources better. Finally, based on the fused knowledge representations, we tailor contextual knowledge-enhanced prompt templates for the CRS to stimulate the reasoning ability of pre-trained language models on dialogue and recommendation tasks. We evaluate the performance of our method on separate evaluation datasets, including the ReDial and the INSPIRED datasets. Based on the Recall, MRR, NDCG, and Distinct evaluation indicators, we demonstrate the effectiveness of the proposed method in dialogue tasks and recommendation tasks. At the same time, we demonstrate that by constructing an interpretable multi-aspect hybrid prompt template, we can effectively mine contextual knowledge from multiple aspects of dialogue.

Transforming construction with innovation in logistics

Marked by rapid urbanization and intense competition, the construction industry faces crucial challenges in addressing urban sustainability. Despite the crucial role of innovations, the construction sector has historically grappled with significant limitations in terms of innovation and productivity, remaining less digitized compared to other industries. The urgent need to accelerate innovation and reduce costs is highlighted by the association between globalization and technological development, underscoring the importance of solutions like Construfrete. With a projected notable growth of 85% in the international construction market by 2030, driven by artificial intelligence and digitization, the urgency of technological adoption in the sector is evident. Construfrete, specifically designed to meet the needs of the Bahia market, aims to optimize the transportation of materials and equipment, enhancing connections between drivers and construction entities. This methodology ensures the app is competitive and responsive, facilitating more efficient and environmentally conscious logistics. Ultimately, Construfrete not only addresses the logistical demands of construction but also boosts efficiency, benefiting drivers, customers, and the local economy in Bahia.

Concrete Aggregate-Gradation Effect and Strength-Criterion Modification for Fully Graded Hydraulic Concrete.

Utilization of large aggregates can promote energy conservation and emissions reductions, and large aggregates have been widely used in hydraulic concrete. The failure criterion for concrete material utilizing large aggregates forms the basis for constitutive models and structural design. However, the concrete failure criterion with respect to large aggregates has never been researched. To this end, the authors first conducted a series of triaxial compressive tests on concrete specimens with scaled aggregates. On this basis, several 3D mesoscopic numerical models were established with different aggregate gradations and used to simulate the triaxial compressive behaviors of hydraulic concrete after the models had been verified by experimental results. The results showed a pronounced aggregate-gradation effect on triaxial compressive behaviors, and concrete mixes with larger aggregates usually have higher compressive strength, especially under conditions of higher confinement. The normalized peak strength can increase by up to 23.49%. Finally, based on the available testing data, the strength criterion in different constitutive models is discussed and modified to allow more accurate simulation of the dynamic responses of and damage to fully graded concrete structures. This result can provide a theoretical basis on which construction entities can optimize the mix proportions of fully graded concrete and detect the failure modes of concrete structures.

Construction Activity Recognition Method Based on Object Detection, Attention Orientation Estimation, and Person Re-Identification

Recognition and classification for construction activities help to monitor and manage construction workers. Deep learning and computer vision technologies have addressed many limitations of traditional manual methods in complex construction environments. However, distinguishing different workers and establishing a clear recognition logic remain challenging. To address these issues, we propose a novel construction activity recognition method that integrates multiple deep learning algorithms. To complete this research, we created three datasets: 727 images for construction entities, 2546 for posture and orientation estimation, and 5455 for worker re-identification. First, a YOLO v5-based model is trained for worker posture and orientation detection. A person re-identification algorithm is then introduced to distinguish workers by tracking their coordinates, body and head orientations, and postures over time, then estimating their attention direction. Additionally, a YOLO v5-based object detection model is developed to identify ten common construction entity objects. The worker’s activity is determined by combining their attentional orientation, positional information, and interaction with detected construction entities. Ten video clips are selected for testing, and a total of 745 instances of workers are detected, achieving an accuracy rate of 88.5%. With further refinement, this method shows promise for a broader application in construction activity recognition, enhancing site management efficiency.

Establishment of Safety Management Measures for Major Construction Workers through the Association Rule Mining Analysis of the Data on Construction Accidents in Korea

Despite increasing industrial advancements, fatal and severe accidents, such as “Falls”, “Struck-by”, “Hit by an object”, “Be crushed”, and “Caught-in/between” accidents, persist in developed countries, including Korea. Various methods, including risk assessment, monitoring systems, technology improvements, and safety education, are being implemented to reduce accidents. However, only a few studies have revealed the causes of accidents and their interrelationships; these studies are based on limited data. Korea recently published accident data using national statistical systems, including the construction safety management integrated information (CSI), enabling the analyses of major accident types. Here, we selected various representative accident cases to minimize the duplication of the data published from 2019 to 2023 and applied the Material, Method, Machine, or Man (4M) analysis method, a risk assessment technique, to perform an accident-type-based association rule mining (ARM) analysis of the accident factors. Through the ARM analysis, we quantitatively identified complex correlations for major accidents. Based on the 4M factors derived through this analysis, we improved a 2–4 model for accident causation and proposed safety management measures for each construction entity.

Influence of activator ratios and concentration on the physio-mechanical and microstructural characteristics of the geopolymers derived from sandstone processing waste.

Natural stones have been utilized to meet various needs of human civilization since ancient times. The exploitation of any resource is associated with the production of redundant materials called wastes. Sandstone waste (SW) is one such waste obtained during the industrial processing of sandstones. Due to its siliceous composition, extensive yield, and disorganized dumping, noxious conditions related to land and human health are promoted. However, the lack of comprehensive engineering studies, mineralogical analysis, and design methodologies associated with the utilization of sandstone processing wastes restricted their applicability only to fillers or partial substitutes with pozzolans and traditional cement in meager volumes. In the past, limited efforts have been made to utilize SW as a construction entity, particularly for binding purposes. Thus, to enhance the scope of its utilization, a comprehensive investigation has been performed in this research to transform sandstone waste into a novel construction material by geopolymerization. Mix design tailoring and laboratory tests were implemented to understand the effects of sodium hydroxide concentration and sodium silicate to sodium hydroxide ratio on the dissolution and physio-mechanical characteristics of SW-based geopolymers. The activator-to-binder ratio was restricted to 0.4 to obtain pastes with sufficient workability without hindering the properties of the matrix. Besides, a high temperature-curing regime was selected based on SW's crystallographic and reactivity analysis. Subsequently, a total of 48 samples were prepared and tested at the curing age of 28 days. Detailed characterization of SW and SW-based geopolymer samples was performed using optical, X-ray, and infrared spectroscopies aided by electron imaging and thermogravimetric techniques. SW-based geopolymer samples showed compressive strengths in the range of 6-12 MPa, ~2 to 3 times higher than those obtained in previous experimentations. Phase analysis and microstructural examinations confirmed SW's participation in geopolymerization. Overall, it could be advocated that geopolymerization is an innovative approach for solving issues related to the disposal and re-utilization of SW, extending its possible application to the fields of cement mixes, wall tiles, mortars, and masonry as per the commendations of ASTM and ACI committee.

Adoption of distributed ledger technology for construction projects: a study of the challenges in a developing country

Purpose The construction industry in Nigeria, like many others worldwide, grapples with increasing demands for enhanced efficiency, transparency and security. While distributed ledger technology (DLT) offers substantial potential in tackling these issues, its implementation faces numerous obstacles. This study aims to investigate the challenges hindering the adoption of DLT within the Nigerian construction sector, capitalizing on a recognized research gap in this field. Design/methodology/approach A comprehensive literature review identified 20 challenges to DLT adoption. A structured questionnaire was developed and distributed to 98 construction professionals selected from a pool of 5,330 members using purposive and snowball sampling. Background information was assessed using frequency and percentage, data normality with the Shapiro–Wilk test and nonparametric data compared using the Kruskal–Wallis H-test. Factor analysis was then used to reduce the challenges into a more coherent set. Findings Findings revealed the top five challenges: power supply issues, data privacy and compliance, an uncertain legal framework, insufficient training and education and a lack of skilled workforce. Further analysis revealed four clusters of challenges, namely, technical and infrastructure barriers, organizational and cultural challenges, financial and economic challenges and regulatory and legal challenges. Practical implications Through the evaluation of challenges and potential strategies to overcome them, this study aims to lay a foundation that assists construction entities in effectively harnessing the benefits of DLT while navigating the obstacles inherent in its adoption. Originality/value This study contributes to the existing body of knowledge by offering insights into the challenges surrounding the adoption of DLT, specifically within the Nigerian construction sector. By juxtaposing the findings from this study with existing research conducted in other countries such as India, South Africa and the USA, a more comprehensive understanding of the challenges unique to the Nigerian context can be gained.

Improving single‐stage activity recognition of excavators using knowledge distillation of temporal gradient data

AbstractSingle‐stage activity recognition methods have been gaining popularity within the construction domain. However, their low per‐frame accuracy necessitates additional post‐processing to link the per‐frame detections. Therefore, limiting their real‐time monitoring capabilities is an indispensable component of the emerging construction of digital twins. This study proposes knowledge DIstillation of temporal Gradient data for construction Entity activity Recognition (DIGER), built upon the you only watch once (YOWO) method and improving its activity recognition and localization performance. Activity recognition is improved by designing an auxiliary backbone to exploit the complementary information in the temporal gradient data (transferred into YOWO using knowledge distillation), while localization is improved primarily through integration of complete intersection over union loss. DIGER achieved a per‐frame activity recognition accuracy of 93.6% and localization mean average precision at 50% of 79.8% on a large custom dataset, outperforming state‐of‐the‐art methods without requiring additional computation during inference, making it highly effective for real‐time monitoring of construction site activities.

Integrate computation intelligence with Bayes theorem into complex construction installation: a heuristic two-stage resource scheduling optimisation approach

The cost control challenge in construction and installation projects has always been a critical concern for construction entities. The complexity of task collaboration among various equipment and nodes during the installation process leads to extended construction duration, resulting in increased construction costs. To address this issue, this paper proposes a heuristic two-stage optimal deployment approach called MERD. The MERD approach incorporates intelligent computing principles from computer science into the resource scheduling of the construction process, modelling the installation scheduling problem into a combinatorial optimisation problem. Designing the probability method based on Bayes theorem, the MERD approach carries out an installation provisioning mechanism to optimise personnel and device allocation in the selected area. As a result, the MERD approach minimises construction hours and reduces labour costs in the construction process. Experimental results demonstrate the effectiveness and efficiency of the MERD approach in reducing work time and cost in engineering projects.

Information Support of Cost Audit in Construction Organizations

This article presents the border between the items of expenses of construction enterprises and their various combinations, as well as the possibilities of showing the results of the works of construction entities, and explains the accounting and description of the income from the subsequent financial and economic activities of the expenses. Information sources of costs are studied.

Research on unbalanced mining of highway project key data based on knowledge graph and cloud model

Various stages of highway project construction process involve text, image, audio, video and other related data sources involving many participants, forming a huge amount of data. Accurately tracing the source of responsibility, refining and applying the unbalanced data in the highway project archives is of great significance for realizing the intelligent transformation of highway construction project management. This paper firstly sorts out the construction process of highway projects and the main data sources, constructs a data association network between construction entities and construction process, as well as a knowledge map of highway construction data. Then, according to the highway construction stage, an index system based on 12 key data is constructed by using the entropy weight cloud model method, and the importance of the data is evaluated. Thirdly, based on the unbalanced characteristics of highway project data, a method of mining big data in highway project archives using classification evaluation indexes is proposed, and the accuracy of this method is verified by case calculation. Finally, taking the Shizong Qiubei Expressway in China as an example, the intelligent management and control suggestions for key data of transportation projects are proposed. It is found that the key data with special importance rate in highway construction include construction data, supervision data and completion data. Boosting algorithm is more accurate than the traditional SMOTE algorithm for unbalanced data mining, which helps to save the project construction cost and improve the quality of data extraction in the project archives. This study provides a theoretical reference for key data traceability of highway project intelligent management and control platform and the improvement of intelligent management efficiency.

Сучасні підходи до управління фінансовими ресурсами житлового будівництва в Україні

The purpose of this article is to study the role of the financial resources management process in ensuring the efficiency of functioning of economic entities of housing construction. The author substantiates the leading role of housing construction in meeting the primary needs of society and forming the key prerequisites for the development of the national economy. The existing approaches to the management of financial resources in modern conditions are generalized, which allowed to emphasize the need to apply a system-synergistic approach in the process of managing financial resources by economic entities in housing construction. Based on a generalization of existing approaches to the interpretation of the essence of the category of «financial resources», the author’s own interpretation of the category of «financial resources of housing construction» is proposed, allowing to highlight their leading role in the formation of financial potential, stimulation of the mechanism for counteracting possible risks and threats in the sphere of housing construction. The author proposes an original approach to building an algorithm for managing the financial resources of economic entities in the housing construction business, which, unlike the existing ones, allows taking into account their type of financial support policy. The necessity of allocating three types of policy of financial support of economic entities in housing construction is substantiated, namely: moderate, offensive, and deterrent. This will ensure the maximum effect of housing development in the long term by combining all available resource components. The author emphasizes the possibility, due to the sufficiency of all types of resources, to facilitate the rapid restoration of housing infrastructure, taking into account the latest innovative approaches to construction and energy saving. The system of the following principles that should become the basis for managing the financial resources of a housing construction entity is proposed: sufficiency, cost minimization, efficiency, financial monitoring and response, variability.

What Influences to Financial Leverage in Listed Construction Firms in Vietnam? The Role of Asset Tangibility and Growth Opportunities

Investment projects in the construction industry usually require a large amount of capital. Most businesses need more capital to implement the investment project; therefore, they use borrowed capital and mobilise capital from investors. Understanding the determinants of excessively low or high leverage among construction companies provides essential information in identifying these companies' financial strategies. This research observes the sample of 53 listed construction entities on the Hanoi Stock Exchange (HNX) in Vietnam, with the 2018-2022 period, to find out what factors impact financial leverage. Statistical data is collected and aggregated from enterprises' audited consolidated financial statements. The author uses financial leverage as a dependent variable, while independent variables include asset tangibility, growth opportunities, profitability, liquidity, firm size and firm age. In addition, GDP and inflation rate are considered as control variables. The author uses OLS, FEM, REM and GLS models, modified Wald test and Wooldridge test to determine the relationship between independent and dependent variables. The research results show that asset tangibility, profitability, liquidity and firm size are statistically significant in explaining the firm's financial leverage change. In contrast, other variables such as growth opportunities, firm age, GDP and inflation were not correlated with the dependence variables. In particular, asset tangibility is the most significant determinant for financial leverage, which means those charged with governance of construction firms should consider carefully before deciding to acquire fixed assets. Based on research findings, the author suggests recommendations for managing financial leverage in construction companies in Vietnam. However, the results of this study will also be helpful for construction companies in other countries.

ПОДАТКОВЕ РЕГУЛЮВАННЯ І СТИМУЛЮВАННЯ РОЗВИТКУ АВІАЦІЙНО-КОСМІЧНОГО КОМПЛЕКСУ НАЦІОНАЛЬНОЇ ЕКОНОМІКИ

The article summarizes the institutional features of taxation of the aviation and space complex by its sub-sectors and individual types of economic activity. The principles of building a tax system for aircraft manufacturing entities, the content of their benefits from VAT, corporate income tax, and land tax are highlighted. The list of their transactions, which are exempt from VAT taxation and taxed at a zero rate, has been systematized. The conditions for exemption from the payment of income tax for aircraft manufacturing entities, the requirements for the targeted use of the released funds and the principles of state control over its legality have been determined. The tax system for aviation transport enterprises has been formalized, which includes benefits from VAT, excise taxes, as well as income tax under contracts of compulsory insurance of passenger transportation of civil aviation. Differences in VAT taxation of international and domestic transportation of passengers and baggage by air transport have been established. The list of its services, which are taxed at zero VAT rate, are exempt from VAT taxation and are not subject to VAT taxation, is defined. The reasons for the application of the excise tax rate without the application of the increasing coefficient for the import and production of aviation gasoline and fuel for jet engines have been clarified. The requirements for registration of tax benefits for transactions with excise goods in terms of the use of tax invoices, excise invoices, sales contracts, etc. are highlighted. Considered possible options for paying off a tax bill for a certain amount of excise tax. The experience of tax incentives for the implementation of the national infrastructural and transport project “Air Express” through the provision of VAT benefits has been systematized. It is substantiated by directions for improving the taxation of the aviation and space complex in terms of: equalization of the tax status of aircraft construction entities and manufacturers of space equipment, the application of a reduced VAT rate for all domestic air transportation, changes in the principles of state financial control of tax benefits based on an audit of the effectiveness of their use.

Real-time Employee Monitoring Technologies in the Construction Sector – Effect, Readiness and Theoretical Perspectives: The case of New Zealand

Varieties of Real-time Employee monitoring Technology (REMT) are becoming popular and have aroused significant interest in recent years from the construction sector, where the industry explores the use of advanced monitoring technologies to reduce unsafe work behaviours and improve productivity. However, studies identified some concerns about applying these monitoring technologies at construction sites. Consequently, REMT devices and applications have not been well-received for tracking frontline workers. Lack of understanding of REMT, monitoring data protection and privacy management strategy set a barrier for the monitoring technologies to implement in the construction industry. Privacy has become a critical issue for the future digital construction site. This study adopts the literature review and a questionnaire survey, examined the readiness, summarised effects of REMT applied at the New Zealand construction sites, identified the influence factors, and discovered the theories that will potentially explain the factors and address the potential impact. Communication Privacy Management theory (CPM), Equity Theory (ET) and Control Theory of Privacy (CTP) are reviewed, and a theoretical framework is built upon REMT adoption in the construction sector. In conclusion, future studies are recommended for the international construction entities to get ready to adopt the real-time monitoring tools.

Synthetic Image Dataset Development for Vision-Based Construction Equipment Detection

This paper presents a systematic method to create universally applicable synthetic training image datasets for computer vision-based construction object detection. The synthetic images created by inserting a virtual object of interest into a real site image allows us to minimize the time and effort for training image data collection and annotation. In addition, the use of synthetic images has an additional benefit that training images can be easily customized for a target construction site by considering the context of the site (e.g., different background scenes, camera positions, and angles) and the possible variability of target objects to be detected (e.g., different sizes, locations, rotation angles, and postures) on images. An automated approach proposed in this study attempts to systematically create the synthetic images using the Unity game engine in which context- and variability-related parameters can be controlled. The proposed method was validated by training a deep learning-based object detection algorithm [i.e., a faster regions with convolutional neural network (R-CNN) model] with synthetic images and testing it on real images from earthwork construction sites to detect an excavator. The CNN models trained with synthetic images showed an average precision value of more than 90%; in particular, the classifier using synthetic images outperformed the one using real site images. The detection results also demonstrated an improved capability to capture the high irregularity of a construction object on images when using techniques of context customization and variability randomization. The findings from this study demonstrate the feasibility and practicality of the use of synthetic images for vision-based approaches in a construction domain. Ultimately, the proposed approach serves as an alternative way to build comprehensive image datasets for construction entities, contributing to facilitating vision-based studies on construction.

건설 하도급계약의 쟁점과 개선방안 - 납품대금 연동제를 중심으로 -

Since subcontracting transactions are characterized by a vertical structure, a superior position in the contractual relationship is premised. Various institutional devices have been prepared to suppress unfair subcontracting transactions caused by these structural problems and to establish a fair subcontracting market environment. However, due to changes in the economy, technological environment, and labor market, many issues are still being raised regarding subcontracting, and a systematic approach is currently under discussion. The Unit Price Adjustment System, which has been actively discussed recently, has also sparked debate about how to share risks between the parties to the subcontracting contract stemmuing from the rise in raw material prices due to unexpected special circumstances such as COVID-19 or the Ukraine crisis. This rise is raw material prices significantly increases the cost of providing the product or service specified in the subcontract; thus if the unit price of delivery is not revised, this will substantially reduce the profit of the subcontractor. Therefore, the Unit Price Adjustment System can be considered as supplementary measure. However, construction is traditionally the field in which subcontracting is used the most. In addition, construction work does not produce standardized products uniformly, unlike normal manufacturing, but requires various types of products according to the demands of the ordering party. Thus, the intermediate products produced by various construction entities participating in the vertical structure of the construction work are closely linked to completion of the final product. After all, in the vertical structure of construction work, cooperation through consultation and coordination among participants is very important. Therefore, it would be desirable to design and operate the legislative policy on the adjustment of subcontract price in such a way that voluntary consultation and mediation between the parties to the contract can be strengthened.

Ameliorating Performance of UAE Projects by Technological Collaboration of Construction Entities

The construction industry is comprised of various entities that are a collection of different teams with varying expertise. These entities are supposed to work together on a particular project to achieve a common goal. This research investigates the association of Information Technology and the Degree of Functional Integration with the performance of Construction Projects. The United Arab Emirates is known for its Construction wonders and mega structures supported by massive investments. Therefore, the construction industry of the United Arab Emirates is selected to study the role Information Technology application in the Performance of the Construction firms when studied together with prevailing function integration norms within the organizations. The collected data is then analyzed through SPSS. It is revealed based on the regression results that Information Technology Capability and Degree of Functional Integration of including entities i.e., Owner, Contractor, and Supplier have positive effects on the performance of Construction projects. In the end findings are supported by a conceptual model that explicitly explains the Procedural levels of Concept implementation.

Collaborative Workflow in an HBIM Project for the Restoration and Conservation of Cultural Heritage

ABSTRACT A restoration and conservation project for a building with heritage values requires an increasingly efficient and sustainable methodology. Based on a collaborative ‘Teamwork’ HBIM (Historic Building Information Modelling) project, this paper aims to describe the technical processes applied to a 16th-century historic building to support an open and interoperable workflow between the participating agents. The process is transparent and controllable by operators and disciplines, ensuring direct and continuous access to project data. The study focuses on implementing effective procedures for the identification and classification of heritage architecture. The first stage comprises the analysis of the geometry and materiality of the existing architecture, using data acquisition technologies such as Terrestrial Laser Scanning (TLS) and Structure-from-Motion (SfM) photogrammetry. The information modelling of the historic building begins with a medium level of knowledge, based on the metric survey and enriched by the materiality of the textures deriving from the point cloud. This enables a modelling approach that fits building components to the real geometry of the historic building, considering the deformations and irregularities that occur over time. In the next phase, the BIM project is developed through the analysis of the construction characteristics, materials, and architectural structuring in the historical evolution of the building. The difference between intervening in architectural heritage and new construction lies in the search for the transposition of construction techniques in walls with a long history, thus requiring classification and sectorisation of the various systems used. It is then required to segment the construction systems based on a semantic study of the walls that make up the envelope of the historic architecture. Programming objects in Python within the BIM platform enables the automated identification processes. The method is applied in the identification of the integrating elements of a larger construction entity, such as the stone ashlars of the masonry wall, and the classification by their construction-temporal dating. The main novelty of this research is the use of the object-oriented programming language (OOP), which automates operations based on an open-source structure and allows the operability of cataloguing, classification, and reuse characteristics.