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Journals / European Journal of Technique (EJT) / 2026 / Cilt: 16 Sayı: 1

Artificial Intelligence for Sustainable Energy Improvements in the Conservation of Cultural Heritage Historic Buildings

Lale Karataş Billor(BURSA TECHNICAL UNIVERSITY)0000-0001-8582-4612
Fatih Ünal(MERSİN ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, MAKİNE MÜHENDİSLİĞİ BÖLÜMÜ, MAKİNE MÜHENDİSLİĞİ PR.)0000-0001-6660-9984
Pages
69–81
Publication Date
2026-07-01
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings indicate a marked acceleration after 2024, although the 2026 data should be interpreted cautiously because they represent only the records indexed up to the search date.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In the conservation process of historic buildings recognized as cultural heritage, the challenge of balancing conservation principles established by international conservation doctrines with energy efficiency has been increasingly emphasized in recent literature.
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Key Findings & Data:Although artificial intelligence-based approaches such as multi-objective optimization, machine learning, digital twins, and Historic Building Information Modeling (HBIM) offer significant potential for addressing this challenge, comprehensive bibliometric evidence specifically focusing on the intersection of artificial intelligence, sustainable energy improvement, and cultural heritage historic buildings remains limited.
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Conclusion & Impact:The findings indicate a marked acceleration after 2024, although the 2026 data should be interpreted cautiously because they represent only the records indexed up to the search date.
🔬Design:Modeling & Simulation
📍Scope:2013 Verileri
⚙️Variables:Historic Buildings · Cultural Heritage · Conservation

Abstract

In the conservation process of historic buildings recognized as cultural heritage, the challenge of balancing conservation principles established by international conservation doctrines with energy efficiency has been increasingly emphasized in recent literature. Although artificial intelligence-based approaches such as multi-objective optimization, machine learning, digital twins, and Historic Building Information Modeling (HBIM) offer significant potential for addressing this challenge, comprehensive bibliometric evidence specifically focusing on the intersection of artificial intelligence, sustainable energy improvement, and cultural heritage historic buildings remains limited. To address this gap, this research conducts a comprehensive bibliometric analysis on a dataset of 122 articles retrieved from the Web of Science Core Collection through a PRISMA-based screening process. Using performance analysis and science mapping techniques, the study examines the period between 2013 and 2026. The findings indicate a marked acceleration after 2024, although the 2026 data should be interpreted cautiously because they represent only the records indexed up to the search date. The field appears to be shaped around four major methodological axes: multi-objective optimization, HBIM and digital twin-based modeling, energy-comfort performance assessment, and sustainable retrofit strategies. The concentration pattern validated through Bradford’s Law (k = 3.19; R² = 0.9839) and Lotka’s Law (β = 4.28; R² = 0.9847) identifies Energy and Buildings as the core journal and highlights research systems centered in Italy, China, and Spain as the leading contributors in the field.

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Cite This Article

Billor, L. K., Ünal, F. (2026). Artificial Intelligence for Sustainable Energy Improvements in the Conservation of Cultural Heritage Historic Buildings. European Journal of Technique (EJT), Cilt: 16 Sayı: 1, 69–81. https://doi.org/10.36222/ejt.1957250

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References (33)

  1. Dal, M., Burkut, E. B., & Karataş, L. (2023). Analysis of Publications on Earthquake Research in Architecture Category and Analysis with R Studio-Biblioshiny Software. Journal of Architectural Sciences and Applications, 8(Special Issue), 183-197. https://doi.org/10.30785/mbud.1333876
  2. Stahel, W. R. (2013). Policy for material efficiency-sustainable taxation as a departure from the throwaway society. Philosophical Transactions of the Royal Society A-Mathematical Physical and Engineering Sciences, 371(1986), Article 20110567. https://doi.org/10.1098/rsta.2011.0567
  3. Ascione, F., Cheche, N., De Masi, R. F., Minichiello, F., & Vanoli, G. P. (2015). Design the refurbishment of historic buildings with the cost-optimal methodology: The case study of a XV century Italian building. Energy and Buildings, 99, 162–176. https://doi.org/10.1016/j.enbuild.2015.04.027
  4. Bruno, S., De Fino, M., & Fatiguso, F. (2018). Historic Building Information Modelling: performance assessment for diagnosis-aided information modelling and management. Automation in Construction, 86, 256–276. https://doi.org/10.1016/j.autcon.2017.11.009
  5. Tejedor, B., Lucchi, E., Bienvenido-Huertas, D., & Nardi, I. (2022). Non-destructive techniques (NDT) for the diagnosis of heritage buildings: Traditional procedures and futures perspectives. Energy and Buildings, 263, Article 112029. https://doi.org/10.1016/j.enbuild.2022.112029
  6. Costa-Carrapico, I., Raslan, R., & Neila Gonzalez, J. (2020). A systematic review of genetic algorithm-based multi-objective optimisation for building retrofitting strategies towards energy efficiency. Energy and Buildings, 210, Article 109690. https://doi.org/10.1016/j.enbuild.2019.109690
  7. Mazzetto, S. (2024). Integrating Emerging Technologies with Digital Twins for Heritage Building Conservation: An Interdisciplinary Approach with Expert Insights and Bibliometric Analysis. Heritage, 7(11), 6432-6479. https://doi.org/10.3390/heritage7110300
  8. Zhang, J., Chan, C. C. C., Kwok, H. H. L., & Cheng, J. C. P. (2023). Multi-indicator adaptive HVAC control system for low-energy indoor air quality management of heritage building preservation. Building and Environment, 246, Article 110910. https://doi.org/10.1016/j.buildenv.2023.110910
  9. Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
  10. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
  11. Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/1094428114562629
  12. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S.,. Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71.
  13. Todorovic, M. S., Ecim-Duric, O., Nikolic, S., Ristic, S., & Polic-Radovanovic, S. (2015). Historic building's holistic and sustainable deep energy refurbishment via BPS, energy efficiency and renewable energy-A case study. Energy and Buildings, 95, 130–137. https://doi.org/10.1016/j.enbuild.2014.11.011
  14. Roberti, F., Oberegger, U. F., Lucchi, E., & Troi, A. (2017). Energy retrofit and conservation of a historic building using multi-objective optimization and an analytic hierarchy process. Energy and Buildings, 138, 1–10. https://doi.org/10.1016/j.enbuild.2016.12.028
  15. Annibaldi, V., Cucchiella, F., De Berardinis, P., Rotilio, M., & Stornelli, V. (2019). Environmental and economic benefits of optimal insulation thickness: A life-cycle cost analysis. Renewable & Sustainable Energy Reviews, 116, Article 109441. https://doi.org/10.1016/j.rser.2019.109441
  16. Semeraro, S., Vecchi, F., Stasi, R., & Berardi, U. (2025). Physics-Informed Neural Networks for predicting indoor temperature and cooling demand in historic buildings. Journal of Building Engineering, 115, Article 114392. https://doi.org/10.1016/j.jobe.2025.114392
  17. Kang, F., Lin, H., Zhou, Z., Ren, Y., Li, X., & Wang, J. (2026). Uncertainty-aware hybrid modeling for spatial thermal forecasting in historic buildings with incomplete structural information. Journal of Building Engineering, 119, Article 115231. https://doi.org/10.1016/j.jobe.2026.115231
  18. Karatzas, S., Lazari, V., Fouseki, K., Pracchi, V. N., & Balaskas, E. (2026). Digital twins-enabled heritage buildings management through social dynamics. Journal of Cultural Heritage Management and Sustainable Development, 16(7), 150–166. https://doi.org/10.1108/JCHMSD-08-2023-0136
  19. Bai, Y., Zhang, Y., Li, Z., Han, W., & Zhang, Y. (2026). Solar collector-integrated liquid dehumidification for historic building retrofit: Feasibility analysis and optimization design in a hot-humid region of China. Applied Thermal Engineering, 289, Article 129810. https://doi.org/10.1016/j.applthermaleng.2026.129810
  20. Salvalaggio, M., Carnieletto, L., Saler, E., Pasut, W., Turrini, U., & Valluzzi, M. R. (2026). Integrating seismic and energy retrofits in built heritage: timber-based solutions within the "nested building" approach. Energy and Buildings, 358, Article 117208. https://doi.org/10.1016/j.enbuild.2026.117208
  21. Ademovic, N., Formisano, A., Penazzato, L., & Oliveira, D. V. (2022). Seismic and energy integrated retrofit of buildings: A critical review. Frontiers in Built Environment, 8, Article 963337. https://doi.org/10.3389/fbuil.2022.963337
  22. Schito, E., Conti, P., & Testi, D. (2018). Multi-objective optimization of microclimate in museums for concurrent reduction of energy needs, visitors' discomfort and artwork preservation risks. Applied Energy, 224, 147–159. https://doi.org/10.1016/j.apenergy.2018.04.076
  23. Schito, E., Conti, P., Urbanucci, L., & Testi, D. (2020). Multi-objective optimization of HVAC control in museum environment for artwork preservation, visitors' thermal comfort and energy efficiency. Building and Environment, 180, Article 107018. https://doi.org/10.1016/j.buildenv.2020.107018
  24. UNESCO. (1972). Convention Concerning the Protection of the World Cultural and Natural Heritage. UNESCO General Conference, 17th Session, Paris. https://whc.unesco.org/en/conventiontext/
  25. ICOMOS. (1964). International Charter for the Conservation and Restoration of Monuments and Sites (The Venice Charter). 2nd International Congress of Architects and Technicians of Historic Monuments, Venice. https://www.icomos.org/images/DOCUMENTS/Charters/venice_e.pdf
  26. European Commission. (2021). A Renovation Wave for Europe — greening our buildings, creating jobs, improving lives. 143rd plenary session, 17-19 March 2021. https://edz.bib.uni-mannheim.de/www-edz/doku/adr/2020/cdr-2020-2786-en.pdf
  27. European Commission. (2019). European Commission Communication: The European Green Deal [COM(2019) 640 final]. https://www.elni.org/fileadmin/elni/dokumente/Green_Deal-Sustainable_Products_Policy_2019-12-18_engl_fin.pdf
  28. European Commission. (2021). ‘Fit for 55’: delivering the EU’s 2030 Climate Target on the way to climate neutrality. Communication from the Commission, COM(2021) 550 final. Brussels: European Commission.
  29. European Parliament and Council. (2024). Directive (EU) 2024/1275 of the European Parliament and of the Council of 24 April 2024 on the energy performance of buildings(recast). Official Journal of the European Union, L series, 8 May 2024.
  30. Unur, K., & Kınıklı, M. A. (2020). Otel Müşterilerine Yönelik Deneyimsel Pazarlamanın Memnuniyete Etkisi: Kapadokya Örneği. Seyahat ve Otel İşletmeciliği Dergisi, 17(3), 378-393. https://doi.org/10.24010/soid.794986
  31. Caner, I. (2025). Comparative study of overheating assessment approaches in university buildings: Impact of different climate zones and shading devices in Turkey. Journal of Building Engineering, 99, 111536. https://doi.org/10.1016/j.jobe.2024.111536
  32. Türkeri, İ. (2022). Dinî Mimaride Doğal Taş Kullanimi: Sancaklar Camii Ve Beylikdüzü Fatma Ana Cemevi. Tasarım Mimarlık Ve Mühendislik Dergisi, 2(1), 1-9. https://izlik.org/JA84JZ85NF
  33. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S.,. Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71.