Аннотації
01.07.2025
Об’єктом дослідження є процес формування висновку будівельно-технічної експертизи системою підтримки процесу відновлення об’єктів нерухомості. Предметом дослідження є моделі і методи штучного інтелекту, що здатні розв’язувати задачу формування експертного висновку щодо категорії технічного стану будівельних конструкцій і об’єктів в цілому. Метою роботи є обґрунтування вибору моделі для розв’язання задачі оцінювання технічного стану об’єктів будівельно-технічної експертизи на основі дослідження моделей і методів штучного інтелекту, що здатні розв’язувати задачу нечіткої класифікації. Для оцінки технічного стану будівельних конструкцій і об’єктів в цілому запропоновано застосовувати дерева рішень з градієнтним прискоренням. Цей метод виправляє помилки попередніх ітерацій і враховує величину різних типів помилок. Показано, що механізм ітеративного навчання дає змогу експертам будівельно-технічної експертизи уточнювати чи доповнювати дані, на основі яких роблять висновки. Коригування висновків ансамблів дерева рішень з градієнтним прискоренням експерти можуть робити відповідно до нормативної бази. Формалізовано вхідні і вихідні дані моделі з урахуванням такого антропогенного фактора, як вплив зброї. Визначено п’ять основних конструктивних елементів, для кожного з яких доцільно навчати ансамблі дерев. Показано функцію втрат, що допомагає приділяти особливу увагу граничним станам будівель і споруд, коли ризик помилки може призвести до повної непридатності або порушення функціонування конструкцій або їхніх елементів. На основі аналізу низки досліджень як предмет подальших досліджень обґрунтовано вибір мультиагентної теорії для забезпечення масштабування і гнучкості системи підтримки процесу відновлення об’єктів нерухомості.
Modern educational infrastructure development faces unprecedented challenges, demanding innovative project management approaches capable of simultaneously ensuring construction efficiency, pedagogical effectiveness, and sustainability goals. Traditional project management methods have proven inadequate for managing the complex stakeholder ecosystems characteristic of educational institutions. Although Building Information Modeling (BIM) and Artificial Intelligence (AI) technologies have demonstrated significant potential in construction management, their integration remains largely unexplored for educational projects. This research develops an integrated AI-driven management model that combines predictive analytics with intelligent Building Information Modeling, specifically tailored for sustainable educational development projects, addressing critical gaps in current approaches through comprehensive platform optimization. The proposed model utilizes a four-layer architecture encompassing a data acquisition infrastructure, an AI analytics engine, intelligent recommendation generation, and proactive control systems. The core innovation lies in an AI-BIM fusion model that creates intelligent building models, which evolve throughout project lifecycles via multi-modal neural networks combining Convolutional Neural Networks (CNNs) for spatial data, temporal analysis networks, and transformer architectures for natural language understanding. Educational space optimization algorithms incorporate evidence-based pedagogical principles to predict the impact of design decisions on learning outcomes, while simultaneously balancing acoustic performance, lighting quality, and sustainability metrics. The system processes multiple information streams, including BIM geometry, educational requirements via Natural Language Processing (NLP), real-time sustainability metrics, and stakeholder communications. Proactive control employs machine learning algorithms, trained on educational project outcomes, to identify early warning indicators and provide predictive intervention strategies through graduated levels of automation. The integrated AI-driven management model represents a paradigm shift in the project management of educational facilities, establishing new frameworks that treat educational outcomes as primary design drivers. Its theoretical contributions extend beyond traditional construction project management, providing validated approaches for holistic intelligence tailored to complex building typologies. The model demonstrates an effective integration of spatial, temporal, and semantic information streams while preserving human-centric decision-making processes, potentially transforming how society designs, delivers, and sustains the built environment.
1. Mohd Saupi, N. D., & Ismail, N. A. (2025). Implementation of 5D building information modelling (BIM) in construction management: Benefits and challenges faced by construction professionals. Built Environment Journal.
2. Honcharenko, T. (2018). The use of BIM-technology to create an information model territories for development. Management of Development of Complex Systems, 33, 131–138.
3. Dolhopolov, S., Honcharenko, T., Terentyev, O., Predun, K., & Rosynskyi, A. (2023). Information system of multi-stage analysis of the building of object models on a construction site. IOP Conference Series: Earth and Environmental Science, 1254.
4. Chernyshev, D., Dolhopolov, S., Honcharenko, T., Sapaiev, V., & Delembovskyi, M. (2022). Digital object detection of construction site based on building information modeling and artificial intelligence systems. International Workshop on Information Technologies: Theoretical and Applied Problems.
5. Dolhopolov, S., Honcharenko, T., Savenko, V., Balina, O., Bezklubenko, I., & Liashchenko, T. (2023). Construction site modeling objects using artificial intelligence and BIM technology: A multi-stage approach. 2023 IEEE International Conference on Smart Information Systems and Technologies (SIST), 174–179.
6. Dolhopolov, S., Honcharenko, T., Terentyev, O., Savenko, V., Rosynskyi, A., Bodnar, N., & Alzidi, E. (2024). Multi-stage classification of construction site modeling objects using artificial intelligence based on BIM technology. 2024 35th Conference of Open Innovations Association (FRUCT), 179–185.
7. Zhang, J., & Jiang, S. (2024). Review of artificial intelligence applications in construction management over the last five years. Engineering, Construction and Architectural Management.
8. Alimi, K., Jin, R., Nguyen, B.N., Nguyen, Q., Chen, W., & Hosking, L. (2025). Exploring artificial intelligence applications in construction and demolition waste management: A review of existing literature. Journal of Science and Transport Technology.
9. Altaie, M. R., & Dishar, M. M. (2024). Integration of artificial intelligence applications and knowledge management processes for construction projects management. Civil Engineering Journal.
10. Francis, M., Perera, S., Zhou, W., & Nanayakkara, S. (2025). Artificial intelligence applications for proactive dispute management in the construction industry: A systematic literature review. Journal of Information Technology in Construction.
11. Berezutskyi, I., Honcharenko, T., Ryzhakova, G., Tykhonova, O., Pokolenko, V., & Sachenko, I. (2024). Methodological approach for choosing type of IT projects management. In 2024 IEEE 4th International Conference on Smart Information Systems and Technologies, 14–19. https://doi.org/10.1109/SIST61555.2024.10629587
12. Chen, J., Lu, W., Ghansah, F.A., & Peng, Z. (2022). Defect digital twinning: A technical framework to integrate robotics, AI and BIM for facility management and renovation. IOP Conference Series: Earth and Environmental Science, 1101.
13. Santos, J. V., Ramos, L., & Mallari, M. (2024). Assessment of facility management performance: A basis for digitalizing reporting systems in educational institutions. Journal of Interdisciplinary Perspectives.
14. Ensafi, M., Alimoradi, S., Gao, X., & Thabet, W. Y. (2022). Machine learning and artificial intelligence applications in building construction: Present status and future trends. Construction Research Congress 2022.
15. Desai, P. D., Sandbhor, S., & Kaushik, A. K. (2023). AI and BIM-based construction defects, rework, and waste optimization. 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), 1–6.
16. Ryzhakova, G., Honcharenko, T., Predun, K., Petrukha, N., Malykhina, O., & Khomenko, O. (2023). Using of fuzzy logic for risk assessment of construction enterprise management system. In 2023 IEEE International Conference on Smart Information Systems and Technologies (SIST), 208–213. https://doi.org/10.1109/SIST58284.2023.10223560
17. Olawumi, T. O., Chan, D. W., Wong, J. S., & Chan, A. P. (2018). Barriers to the integration of BIM and sustainability practices in construction projects: A Delphi survey of international experts. Journal of Building Engineering.
18. Goel, A., Ganesh, L.S., & Kaur, A. (2019). Sustainability integration in the management of construction projects: A morphological analysis of over two decades’ research literature. Journal of Cleaner Production.
19. Abbasnejad, B., Soltani, S., Karamoozian, A., & Gu, N. (2024). A systematic literature review on the integration of industry 4.0 technologies in sustainability improvement of transportation construction projects: State-of-the-art and future directions. Smart and Sustainable Built Environment.
20. Xian, W., Yu, K., Han, F., Fang, L. S., He, D. L., & Han, Q. (2024). Advanced manufacturing in Industry 5.0: A survey of key enabling technologies and future trends. IEEE Transactions on Industrial Informatics, 20 (1), 1055–1068.
21. Chernyshev D., Dolhopolov S., Honcharenko T., Haman H., Ivanova T., Zinchenko M. (2022). Integration of Building Information Modeling and Artificial Intelligence Systems to Create a Digital Twin of the Construction Site, 2022 IEEE 17th International Conference on Computer Sciences and Information Technologies (CSIT), pp. 36–39. DOI: 10.1109/CSIT56902.2022.10000717.
1. Mohd Saupi, N. D., & Ismail, N. A. (2025). Implementation of 5D building information modelling (BIM) in construction management: Benefits and challenges faced by construction professionals. Built Environment Journal.
2. Honcharenko, T. (2018). The use of BIM-technology to create an information model territories for development. Management of Development of Complex Systems, 33, 131–138.
3. Dolhopolov, S., Honcharenko, T., Terentyev, O., Predun, K., & Rosynskyi, A. (2023). Information system of multi-stage analysis of the building of object models on a construction site. IOP Conference Series: Earth and Environmental Science, 1254.
4. Chernyshev, D., Dolhopolov, S., Honcharenko, T., Sapaiev, V., & Delembovskyi, M. (2022). Digital object detection of construction site based on building information modeling and artificial intelligence systems. International Workshop on Information Technologies: Theoretical and Applied Problems.
5. Dolhopolov, S., Honcharenko, T., Savenko, V., Balina, O., Bezklubenko, I., & Liashchenko, T. (2023). Construction site modeling objects using artificial intelligence and BIM technology: A multi-stage approach. 2023 IEEE International Conference on Smart Information Systems and Technologies (SIST), 174–179.
6. Dolhopolov, S., Honcharenko, T., Terentyev, O., Savenko, V., Rosynskyi, A., Bodnar, N., & Alzidi, E. (2024). Multi-stage classification of construction site modeling objects using artificial intelligence based on BIM technology. 2024 35th Conference of Open Innovations Association (FRUCT), 179–185.
7. Zhang, J., & Jiang, S. (2024). Review of artificial intelligence applications in construction management over the last five years. Engineering, Construction and Architectural Management.
8. Alimi, K., Jin, R., Nguyen, B.N., Nguyen, Q., Chen, W., & Hosking, L. (2025). Exploring artificial intelligence applications in construction and demolition waste management: A review of existing literature. Journal of Science and Transport Technology.
9. Altaie, M. R., & Dishar, M. M. (2024). Integration of artificial intelligence applications and knowledge management processes for construction projects management. Civil Engineering Journal.
10. Francis, M., Perera, S., Zhou, W., & Nanayakkara, S. (2025). Artificial intelligence applications for proactive dispute management in the construction industry: A systematic literature review. Journal of Information Technology in Construction.
11. Berezutskyi, I., Honcharenko, T., Ryzhakova, G., Tykhonova, O., Pokolenko, V., & Sachenko, I. (2024). Methodological approach for choosing type of IT projects management. In 2024 IEEE 4th International Conference on Smart Information Systems and Technologies, 14–19. https://doi.org/10.1109/SIST61555.2024.10629587
12. Chen, J., Lu, W., Ghansah, F.A., & Peng, Z. (2022). Defect digital twinning: A technical framework to integrate robotics, AI and BIM for facility management and renovation. IOP Conference Series: Earth and Environmental Science, 1101.
13. Santos, J. V., Ramos, L., & Mallari, M. (2024). Assessment of facility management performance: A basis for digitalizing reporting systems in educational institutions. Journal of Interdisciplinary Perspectives.
14. Ensafi, M., Alimoradi, S., Gao, X., & Thabet, W. Y. (2022). Machine learning and artificial intelligence applications in building construction: Present status and future trends. Construction Research Congress 2022.
15. Desai, P. D., Sandbhor, S., & Kaushik, A. K. (2023). AI and BIM-based construction defects, rework, and waste optimization. 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), 1–6.
16. Ryzhakova, G., Honcharenko, T., Predun, K., Petrukha, N., Malykhina, O., & Khomenko, O. (2023). Using of fuzzy logic for risk assessment of construction enterprise management system. In 2023 IEEE International Conference on Smart Information Systems and Technologies (SIST), 208–213. https://doi.org/10.1109/SIST58284.2023.10223560
17. Olawumi, T. O., Chan, D. W., Wong, J. S., & Chan, A. P. (2018). Barriers to the integration of BIM and sustainability practices in construction projects: A Delphi survey of international experts. Journal of Building Engineering.
18. Goel, A., Ganesh, L.S., & Kaur, A. (2019). Sustainability integration in the management of construction projects: A morphological analysis of over two decades’ research literature. Journal of Cleaner Production.
19. Abbasnejad, B., Soltani, S., Karamoozian, A., & Gu, N. (2024). A systematic literature review on the integration of industry 4.0 technologies in sustainability improvement of transportation construction projects: State-of-the-art and future directions. Smart and Sustainable Built Environment.
20. Xian, W., Yu, K., Han, F., Fang, L. S., He, D. L., & Han, Q. (2024). Advanced manufacturing in Industry 5.0: A survey of key enabling technologies and future trends. IEEE Transactions on Industrial Informatics, 20 (1), 1055–1068.
21. Chernyshev D., Dolhopolov S., Honcharenko T., Haman H., Ivanova T., Zinchenko M. (2022). Integration of Building Information Modeling and Artificial Intelligence Systems to Create a Digital Twin of the Construction Site, 2022 IEEE 17th International Conference on Computer Sciences and Information Technologies (CSIT), pp. 36–39. DOI: 10.1109/CSIT56902.2022.10000717.