Integrated model of commercial complex design in modern urban planning using artificial intelligence based on the teachings of Iranian markets and industry 6
Reza Torkaman
1
(
Department of Management, Najafabad Branch, Islamic Azad University, Najafabad, Iran
)
سید مهدی ابطحی
2
(
)
zahra rezaei
3
(
Department of Computer Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
)
ahmad torkaman
4
(
architecture group , marvdasht unit , islamic azad university
)
Keywords: Commercial Complex Design, Artificial Intelligence, Iranian Architecture, Industry 6, Layout Optimization,
Abstract :
Commercial complexes play a pivotal role in urban development, serving as key hubs for economic and social interactions. With the advancement of modern technologies and the emergence of Industry 6, which encompasses innovations such as the Internet of Things, artificial intelligence, and blockchain, the need for transformation in the design and management of these complexes has become increasingly evident. Despite the potential of new technologies to enhance the efficiency and flexibility of commercial complexes, little attention has been paid to integrating Iranian architectural principles with AI algorithms to improve the design and management of these centers. This research aims to propose a comprehensive model for designing commercial complexes by leveraging AI and traditional Iranian architecture principles, thereby enhancing efficiency and creating spaces with a native identity that meet both current and future needs.
Classified as a quantitative and applied study, this research employs artificial neural network modeling to optimize the layout of cellular units and architectural spaces. Architectural data and constraints are fed into the model, and AI algorithms are used to develop an optimal design. The findings reveal that combining traditional Iranian architectural principles with AI leads to the creation of unique, flexible spaces that not only meet contemporary demands but also adapt to future technologies and Industry 6 infrastructures. The results indicate that, in addition to preserving cultural identity and enhancing the sustainability of complexes, this model can serve as a framework for designers and managers of commercial complexes to improve efficiency and align with future urban needs.
Akinosho, T.D.; Oyedele, L.O.; Bilal, M.; Ajayi, A.O.; Delgado, M.D.; Akinade, O.O.; Ahmed, A.A. Deep Learning in the Construction Industry: A Review of Present Status and Future Innovations. J. Build. Eng. 2020, 32, 101827.
Almusaed, A.; Almssad, A.; Yitmen, I.; Homod, R.Z. Enhancing Student Engagement: Harnessing “AIED”’s Power in Hybrid Education—A Review Analysis. Educ. Sci. 2023, 13, 632.
Alshaikhi, A.; Khayyat, M. An Investigation into the Impact of Artificial Intelligence on the Future of Project Management. In Proceedings of the 2021 International Conference of Women in Data Science at Taif University, WiDSTaif 2021, Taif, Saudi Arabia, 30–31 March 2021.
Al-subhi, S.H.; Papageorgiou, E.I.; Pérez, P.P.; Mahdi, G.S.S.; Acuña, L.A. Triangular Neutrosophic Cognitive Map for Multistage Sequential Decision-Making Problems. Int. J. Fuzzy Syst. 2021, 23, 657–679.
Amer, F.; Jung, Y.; Golparvar-Fard, M. Transformer Machine Learning Language Model for Auto-Alignment of Long-Term and Short-Term Plans in Construction. Autom. Constr. 2021, 132, 103929.
Auth, G.; Johnk, J.; Wiecha, D.A. A Conceptual Framework for Applying Artificial Intelligence in Project Management. In Proceedings of the 2021 IEEE 23rd Conference on Business Informatics, CBI 2021—Main Papers, Bolzano, Italy, 1–3 September 2021; Volume 1, pp. 161–170.
Bento, S.; Pereira, L.; Gonçalves, R.; Dias, Á.; da Costa, R.L. Artificial Intelligence in Project Management: Systematic Literature Review. Int. J. Technol. Intell. Plan. 2022, 13, 143–163.
Breque, M.; De Nul, L.; Petrides, A.; European Commission. Directorate-General for Research and Innovation. In Industry 5.0: Towards a Sustainable, Human-Centric and Resilient European Industry; European Commission, Directorate-General for Research and Innovation: Luxembourg, 2021; ISBN 9789276253082.
C¯ırule, D.; B¯erziša, S. Use of Chatbots in Project Management. Commun. Comput. Inf. Sci. 2019, 1078, 33–43.
Cheng, M.Y.; Cao, M.T.; Herianto, J.G. Symbiotic Organisms Search-Optimized Deep Learning Technique for Mapping Construction Cash Flow Considering Complexity of Project. Chaos Solitons Fractals 2020, 138, 109869.
Cheng, M.Y.; Cao, M.T.; Jaya Mendrofa, A.Y. Dynamic Feature Selection for Accurately Predicting Construction Productivity Using Symbiotic Organisms Search-Optimized Least Square Support Vector Machine. J. Build. Eng. 2021, 35, 101973.
Customer Experience and Store Efficiency. AKSEN: Journal of Design and Creative Industry, 9 (1), halaman 17-29. https:10.37715/aksen.v9i1.4819
Darko, A.; Chan, A.P.C.; Adabre, M.A.; Edwards, D.J.; Hosseini, M.R.; Ameyaw, E.E. Artificial Intelligence in the AEC Industry: Scientometric Analysis and Visualization of Research Activities. Autom. Constr. 2020, 112, 103081.
de Oliveira, M.A.; Pacheco, A.S.; Futami, A.H.; Valentina, L.V.O.D.; Flesch, C.A. Self-Organizing Maps and Bayesian Networks in Organizational Modelling: A Case Study in Innovation Projects Management. Syst. Res. Behav. Sci. 2023, 40, 61–87.
de Oliveira, R.A.; Hipólito, G.M.B.; Pontes, R.D.F.F.; Ferreira, P.H.N.; Moreira, R.S.; Plácido, J.; Silva,
Duraiswamy, A.; Selvam, G. An Ant Colony-Based Optimization Model for Resource-Leveling Problem. Lect. Notes Civ. Eng. 2022, 191, 333–342.
Dwivedi, Y.K.; Kshetri, N.; Hughes, L.; Slade, E.L.; Jeyaraj, A.; Kar, A.K.; Baabdullah, A.M.;
Ebrahimzadeh, N. (2024). An Architectural Plugin: Design, Innovation and Technology in Iranian Architecture. Universitat Politècnica de Catalunya.
Ejjami, R., & Rahim, N. (2024). Retail 5.0: Creating Resilient and Customer-Centric Shopping Experiences through Advanced Technologies. International Journal for Multidisciplinary Research, 6(4), 1-15.
Eswaran, U., Eswaran, V., Eswaran, V., & Murali, K. (2024). Empowering the factory of the future: Integrating artificial intelligence, machine learning, and IoT innovations in Industry 6.0. In Evolution and Advances in Computing Technologies for Industry 6.0 (1st ed., pp. 21). CRC Press. https://doi.org/10.1201/9781003503934.
Ghansah, F.A.; Lu,W. A scientometric and content analysis are significant opportunities for digital twins for smart buildings. Smart Sustain. Built Environ. 2023. ahead-of-print.
Hofmann, P.; Jöhnk, J.; Protschky, D.; Urbach, N. Developing Purposeful AI Use Cases—A Structured Method and Its Application In Project Management. In WI2020 Zentrale Tracks; GITO Verlag: Berlin, Germany, 2020; pp. 33–49.
Holzmann, V.; Zitter, D.; Peshkess, S. The Expectations of Project Managers from Artificial Intelligence: A Delphi Study. Proj. Manag. J. 2022, 53, 438–455.
Ikudayisi, A.E.; Chan, A.P.; Darko, A.; Yomi, M.D. Integrated practices in the Architecture, Engineering, and Construction industry: Current Scope and Pathway towards Industry 5.0. J. Build. Eng. 2023, 73, 106788.
Karan, E.; Safa, M.; Suh, M.J. Use of Artificial Intelligence in a Regulated Design Environment—A Beam Design Example. Lect. Notes Civ. Eng. 2021, 98, 16–25.
153. Miller, G. Artificial Intelligence Project Success Factors: Moral Decision-Making with Algorithms. In Proceedings of the 16th Conference on Computer Science and Intelligence Systems, Sofia, Bulgaria, 26 September 2021; pp. 379–390. Hsu, H.C.; Chang, S.; Chen, C.C.; Wu, I.C. Knowledge-Based System for Resolving Design Clashes in Building Information Models. Autom. Constr. 2020, 110, 103001. Hamada, M.A.; Abdallah, A.; Kasem, M.; Abokhalil, M. Neural Network Estimation Model to Optimize Timing and Schedule Of Software Projects. In Proceedings of the SIST 2021—2021 IEEE International Conference on Smart Information Systems and Technologies, Nur-Sultan, Kazakhstan, 28–30 April 2021.
Kuster, L. The Current State and Trends of Artificial Intelligence in Project Management: A Bibliometric Analysis. Master Thesis, Escola de Administração de Empresas de São Paulo, São Paulo, Brazil, 2021.
Makaula, S.; Munsamy, M.; Telukdarie, A. Impact of Artificial Intelligence in South African Construction Project Management Industry. In Proceedings of the International Conference on Industrial Engineering and Operations Management, Sao Paulo, Brazil, 5–8 April 2021; IEOM Society International: Sao Paulo, Brazil, 2021; pp. 148–162.
Minerva, et al (2024). Elements of Retail Store Interior Design: A Qualitative Study on Enhancing
Oliveira, B.A.S.; De Faria Neto, A.P.; Fernandino, R.M.A.; Carvalho, R.F.; Fernandes, A.L.; Guimaraes, F.G. Automated Monitoring Of Construction Sites of Electric Power Substations Using Deep Learning. IEEE Access 2021, 9, 19195–19207.
Relich, M.; Nielsen, I. Estimating Production and Warranty Cost at the Early Stage of a New Product Development Project. IFAC-PapersOnLine 2021, 54, 1092–1097.
Ruiz, J.G.; Torres, J.M.; Crespo, R.G. The Application of Artificial Intelligence in Project Management Research: A Review. Int. J. Interact. Multimed. Artif. Intell. 2021, 6, 54–66.
Senjak Pejić, M. et al. (2023). Improving construction projects and reducing risk by using artificial intelligence Social informatics journal, 2(1), 33-40.
Subbiah, P., Tyagi, A. K., & Mazumdar, B. D. (2024). The future of manufacturing and artificial intelligence: Industry 6.0 and beyond. In Industry 4.0, Smart Manufacturing, and Industrial Engineering (pp. 16). CRC Press. https://doi.org/10.1201/9781003473886.
Taboada, I.; Daneshpajouh, A.; Toledo, N.; de Vass, T. Artificial Intelligence Enabled Project Management: A Systematic Literature Review. Appl. Sci. 2023, 13, 5014.
Wu, C.; Li, X.; Guo, Y.; Wang, J.; Ren, Z.; Wang, M.; Yang, Z. Natural Language Processing for Smart Construction: Current Status In addition, Future Directions. Autom. Constr. 2022, 134, 104059.
Xiong, Z.; Gan, X.; Li, Y.; Ding, D.; Geng, X.; Gao, Y. Application of Smart Substation Site Management System Based on 3D Digitization. J. Phys. Conf. Ser. 2021, 1983, 012086.