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International Journal of BIM and Engineering Science
Volume 6 , Issue 2, PP: 39-54 , 2023 | Cite this article as | XML | Html |PDF

Title

Application of Artificial Intelligence Tools with BIM Technology in Construction Management: Literature Review

  Ali Louai Mostafa 1 * ,   Mohamed Ali Mohamed 2 ,   Sonia Ahmed 3 ,   Waleed Mahfouz M. A. Youssef 4

1  Student of Master program in Building Information Modeling and Management at Syrian Virtual University Damascus Syria
    (ali_157357@svuonline.org)

2  Lecturer Professor, Building Information Modelling and Management Master Program, Syrian Virtual University, Damascus, Syria
    (mhamadtop@gmail.com)

3  Lecturer Professor at the Faculty of Engineering, Al-Rasheed University,and Building Information Modelling and Management Master Program, Syrian Virtual University, Damascus, Syria
    (Sonia_ahmed@ru.edu.sy)

4  Structural Engineering, Faculty of Engineering, Cairo University, Giza, Egypt
    (cvlmaster@yahoo.com)

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Doi   :   https://doi.org/10.54216/IJBES.060203

Received: November 11, 2022 Revised: January 08, 2022 Accepted: March 17, 2023

Abstract :

Nowadays, the construction sector industry energizes all other industries to diversify their service areas, nonetheless this sector needs to keep leading with technological developments. Following the adoption of Building Information Modeling technology (BIM), the construction projects has become more controlled and coordinated, which has contributed to improve productivity rates and to rationalize resources usage. This research is studied the developments in construction, especially technologies that adopt artificial intelligence (AI) with BIM technology such as machine learning, Augmented Reality techniques (AR), digital assistants, robots, automatic planning, scheduling, and optimization. These techniques can be used during design and construction stages to improve collaborative processes that have become a cornerstone of BIM technologies, as well as financial control and scheduling. Through using BIM, the construction industry can adopt AI technologies like autonomous systems and rely on machine learning in project management to access AI-based project self-management.

Keywords :

Artificial Intelligence (AI); AEC (Architecture; Engineering; and Construction);  Building Information Modelling (BIM); Augmented Reality (AR); Autonomous

References :

[1] Safour, R., Ahmed, S. & Zaarour, B., 2021. BIM Adoption around the World. International Journal of BIM and Engineering Science, 4(2), pp. 49-63.

[2] Yusof, N., Ishak, S. & Doheim, R., 2018. An Exploratory Study of Building Information Modelling Maturity in the Construction Industry. International Journal of BIM and Engineering Science, 1(1), pp. 6-19.

[3] Elhendawi, A., 2018. Methodology for BIM Implementation in KSA in AEC Industry. Master of Science MSc in Construction Project Management ed. Edinburgh, UK: Edinburgh Napier University, UK.

[4] Shaban, M. & Elhendawi, A., 2018. Building Information Modeling in Syria: Obstacles and Requirements for Implementation. International Journal of BIM and Engineering Science, 1(1), pp. 42-64.

[5] Banawi, A., Aljobaly, O. & Ahiable, C., 2019. A Comparative Review of Building Information Modeling Frameworks. International Journal of BIM and Engineering Science, 2(2), pp. 23-49.

[6] Elhendawi, A., Smith, A. & Elbeltagi, E., 2019. Methodology for BIM implementation in the Kingdom of Saudi Arabia. International Journal of BIM and Engineering Science, 2(1), pp. 1-21.

[7] Hamma-adama, M., Kouider, T. & Salman, H., 2020. Analysis of barriers and drivers for BIM adoption. International journal of BIM and engineering science, 3(1), pp. 18-41.

[8] Ahmed, S., Dlask, P., Selim, O. & Elhendawi, A., 2018. BIM Performance Improvement Framework for Syrian AEC Companies. International Journal of BIM and Engineering Science, 1(1), pp. 21-41.

[9] Elhendawi, A., Omar, H., Elbeltagi, E. & Smith, A., 2020. Practical approach for paving the way to motivate BIM non-users to adopt BIM. International Journal of BIM and Engineering Science, 2(2), pp. 1-22.

[10] Salamah, T., Shibani, A., & Alothman, K. (2023). Improving AEC Project Performance in Syria Through the Integration of Earned Value Management System and Building Information Modelling: A case Study. International Journal of BIM and Engineering Science, 6(1), pp: 74-95. DOI: https://doi.org/10.54216/IJBES.060105.

[11] Lepkova, N., Maya, R., Ahmed, S. & Šarka, V., 2019. BIM Implementation Maturity Level and Proposed Approach for the Upgrade in Lithuania. International Journal of BIM and Engineering Science, 2(1), pp. 22-38.

[12] Evans, M., Farrell, P., Elbeltagi, E., Mashali, A. and Elhendawi, A., 2020. Influence of partnering agreements associated with BIM adoption on stakeholder's behaviour in construction mega-projects. International Journal of BIM and Engineering Science, 3(1), pp.1-20.

[13] Ghedas, H., 2021. Skylight as a passive design strategy in Tunisian dwelling using BIM technology. International Journal of BIM and Engineering Science, 4(1), pp. 18-25.

[14] Elgendi, A., Elhendawi, A., Youssef, W. & Darwish, A., 2021. The Vulnerability of the Construction Ergonomics to Covid-19 and Its Probability Impact in Combating the Virus. International Journal of BIM and Engineering Science, 4(1), pp. 1-19.

[15] Ghedas, H., 2021. Trombe wall as a passive design strategy in Tunisian dwelling using BIM technology. International Journal of BIM and Engineering Science, 4(2), pp. 79-89.

[16] Zaarour, B. & Mayhoub, N., 2021. Effect of needle diameters on the diameter of electrospun PVDF nanofibers. International Journal of BIM and Engineering Science, 4(2), pp. 26-32.

[17] Abd Alnoor, B., 2022. BIM model for railway intermediate station: transportation perspective. International Journal of BIM and Engineering Science, 4(2), pp. 33-48.

[18] Al Hammoud, E., 2021. Comparing BIM Adoption Around The World, Syria’s Current Status and Future. International Journal of BIM and Engineering Science, 4(2), pp. 64-78.

[19] Mashali, A. & El tantawi, A., 2022. BIM-based stakeholder information exchange (IE) during the planning phase in smart construction megaprojects (SCMPs). International Journal of BIM and Engineering Science, 5(1), pp. 08-19.

[20] Dutt, V. (2020, April 8). AEC Industry Trends: How BIM is Leading the Future of Building Design. Convergence. https://projectdelivery.autodesk.com/blog/aec-industry-trends-bim-dodge-analytics/

[21] Andrea Sestino & Andrea De Mauro (2022) Leveraging Artificial Intelligence in Business: Implications, Applications and Methods, Technology Analysis & Strategic Management, 34:1, 16-29, DOI: 10.1080/09537325.2021.1883583

[22] Andrea Sestino & Andrea De Mauro (2021), “Leveraging Artificial Intelligence in Business: Implications, Applications and Methods”, Technology Analysis & Strategic Management, DOI: 10.1080/09537325.2021.1883583

[23] Vandezande, J. (2021). Status of BIM adoption in the US. Building Smart. Retrieved April 2021, from https://www.buildingsmart.org/wp-content/uploads/2019/03/Status-of-BIM-Adoption-in-the-US-James-Vandezande.pdf

[24] Salami, H. & Alothman, K., 2022. Engineering Training and its Importance for Building Information Modelling. International Journal of BIM and Engineering Science, 5(1), pp. 41-60.

[25] Al Hammoud, E. & Ahmed, S., 2022. Submitting BIM to the Educational Plan for the Faculty of Architecture According to NARS and ARS Standards. International Journal of BIM and Engineering Science, 5(1), pp. 20-40.

[26] Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine Bias. Pro Publica. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.

[27] Brock, D. (2018). Learning from Artificial Intelligence’s Previous Awakenings: The History of Expert Systems. AI Magazine 39(3), 3-15.

[28] Collins, H. (1992). Artificial Experts: Social Knowledge and Intelligent Machines. Cambridge, MA: MIT Press.

[29] Sacks, R., Eastman, C.M., Lee, G., Teicholz, P., 2018. BIM Handbook: A Guide to Building Information Modeling for Owners, Designers, Engineers, Contractors and Facility Managers. John Wiley and Sons, Hoboken, NJ.

[30] Sacks, R., Bloch, T., Katz, M., Yosef, R., 2019. Automating design review with artificial intelligence and BIM: state of the art and research framework. In: Behzadan, A.H., Cho, Y., Leite, F., Wang, C. (Eds.), Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation. American Society of Civil Engineers, Atlanta, GA, USA, pp. 353–360.

[31] Sacks, R., Ma, L., Yosef, R., Borrmann, A., Daum, S., Kattel, U., 2017. Semantic enrichment for building information modeling: procedure for compiling inference rules and operators for complex geometry. J. Comput. Civ. Eng. 31 (6), 04017062 https://doi.org/10.1061/(ASCE)CP.1943-5487.0000705.

[32] Sacks, R., Navon, R., Brodetskaia, I., 2006. Interpretation of automatically monitored equipment data in construction control. J. Comput. Civ. Eng. 20, 111–120. https:// doi.org/10.1061/(ASCE)0887-3801(2006)20:2(111).

[33] Song, J., Kim, J., Lee, J.-K., 2018. NLP and Deep Learning-Based Analysis of Building Regulations to Support Automated Rule Checking System, 7.

[34] Trimble, 2020. “Trimble XR10 with Hololens 2.” Trimble mixed reality. https://mixedr eality.trimble.com/.

[35] Turk, Z., Isakovic, T., Fischinger, M., 1994. Object-oriented modeling of design system for RC buildings. J. Comput. Civ. Eng. 8, 436–453.

[36] Wang, X., Kim, M.J., Love, P.E.D., Kang, S.-C., 2013. Augmented Reality in built environment: classification and implications for future research. Autom. ConStruct. 32, 1–13.

[37] Al Qady, M., Kandil, A., 2010. Concept relation extraction from construction documents using natural language processing. J. Construct. Eng. Manag. 136 (3), 294–302.

[38] Andersen, K., Forr, T., 2018. The State of Construction Technology. Jones Lang LaSalle IP, Inc., p. 12

[39] Azevedo, M.A., 2019. Investor Momentum Builds for Construction Tech. Crunchbase News, San Francisco, CA.

[40] Ballard, G., 2000. The Last Planner System of Production Control. PhD Dissertation. University of Birmingham, Birmingham, U.K.

[41] Ballard, G., 2008. The lean project delivery system: an update. Lean Constr. J. 2008, 1–19.

[42] Bekkelien, A., Deriaz, M., Marchand-Maillet, S., 2012. “Bluetooth Indoor positioning.” Master's Thesis. University of Geneva.

[43] Belsky, M., Sacks, R., Brilakis, I., 2016. Semantic enrichment for building information modeling. Comput. Aided Civ. Infrastruct. Eng. 31 (4), 261–274. https://doi.org/ 10.1111/mice.12128.

[44] Bishop, C.M., 2016. Pattern Recognition and Machine Learning. Information Science and Statistics. Springer, New York, New York, NY.

[45] L. Wright, S. Davidson, How to tell the difference between a model and a digital twin, Adv. Model. Simulat. Eng. Sci. 7 (2020) 13, https://doi.org/10.1186/s40323-020-00147-4.

[46] E. Negri, L. Fumagalli, M. Macchi, A Review of the Roles of Digital Twin in CPSbased Production Systems, Procedia Manuf. 11 (2017) 939–948, https://doi.org/10.1016/j.promfg.2017.07.198.

[47] Blanco, J.L., Mullin, A., Pandya, K., Sridhar, M., 2017. The New Age of Engineering and Construction Technology. McKinsey & Company, Philadelphia, PA.

[48] Bloch, T., Katz, M., Yosef, R., Sacks, R., 2019. Automated Model Checking for Topologically Complex Code Requirements – Security Room Case Study. In: O’Donnell, J. (Ed.), 2019 European Conference on Computing in Construction. EC3, Chania, Crete, Greece.

[49] Bloch, T., Sacks, R., 2018. Comparing machine learning and rule-based inferencing for semantic enrichment of BIM models. Autom. ConStruct. 91, 256–272. https:// doi.org/10.1016/j.autcon.2018.03.018.

[50] Davila Delgado, J. M., & Oyedele, L. (2021). Digital Twins for the built environment: Learning from conceptual and process models in manufacturing. Advanced Engineering Informatics, 49, 101332. https://doi.org/10.1016/j.aei.2021.101332.

 

Cite this Article as :
Style #
MLA Ali Louai Mostafa, Mohamed Ali Mohamed, Sonia Ahmed, Waleed Mahfouz M. A. Youssef. "Application of Artificial Intelligence Tools with BIM Technology in Construction Management: Literature Review." International Journal of BIM and Engineering Science, Vol. 6, No. 2, 2023 ,PP. 39-54 (Doi   :  https://doi.org/10.54216/IJBES.060203)
APA Ali Louai Mostafa, Mohamed Ali Mohamed, Sonia Ahmed, Waleed Mahfouz M. A. Youssef. (2023). Application of Artificial Intelligence Tools with BIM Technology in Construction Management: Literature Review. Journal of International Journal of BIM and Engineering Science, 6 ( 2 ), 39-54 (Doi   :  https://doi.org/10.54216/IJBES.060203)
Chicago Ali Louai Mostafa, Mohamed Ali Mohamed, Sonia Ahmed, Waleed Mahfouz M. A. Youssef. "Application of Artificial Intelligence Tools with BIM Technology in Construction Management: Literature Review." Journal of International Journal of BIM and Engineering Science, 6 no. 2 (2023): 39-54 (Doi   :  https://doi.org/10.54216/IJBES.060203)
Harvard Ali Louai Mostafa, Mohamed Ali Mohamed, Sonia Ahmed, Waleed Mahfouz M. A. Youssef. (2023). Application of Artificial Intelligence Tools with BIM Technology in Construction Management: Literature Review. Journal of International Journal of BIM and Engineering Science, 6 ( 2 ), 39-54 (Doi   :  https://doi.org/10.54216/IJBES.060203)
Vancouver Ali Louai Mostafa, Mohamed Ali Mohamed, Sonia Ahmed, Waleed Mahfouz M. A. Youssef. Application of Artificial Intelligence Tools with BIM Technology in Construction Management: Literature Review. Journal of International Journal of BIM and Engineering Science, (2023); 6 ( 2 ): 39-54 (Doi   :  https://doi.org/10.54216/IJBES.060203)
IEEE Ali Louai Mostafa, Mohamed Ali Mohamed, Sonia Ahmed, Waleed Mahfouz M. A. Youssef, Application of Artificial Intelligence Tools with BIM Technology in Construction Management: Literature Review, Journal of International Journal of BIM and Engineering Science, Vol. 6 , No. 2 , (2023) : 39-54 (Doi   :  https://doi.org/10.54216/IJBES.060203)
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