Investigação das aplicações integradas de inteligência artificial e BIM na industria da construção civil

Autores

DOI:

https://doi.org/10.46421/sbtic.v4i00.2409

Palavras-chave:

Inteligência Artificial, BIM, Benefícios, Tecnologia, Construção Civil

Resumo

As tecnologias digitais avançam incorporando modelagens baseadas em Inteligência Artificial (IA), ao passo que a Construção Civil aplica o Modelagem da Informação da Construção (BIM). Nesse contexto, este artigo tem como objetivo identificar quais são os principais benefícios e desafios da integração entre BIM e IA discutindo também as direções para pesquisas futuras. Para isso, aplica-se uma revisão sistemática da literatura que compreende a aplicação de bibliometria e análise de conteúdo em 166 artigos indexados na Scopus e Web of Science. Os resultados desta pesquisa mostram que a literatura explora e atesta a viabilidade da automação dos processos de projeto com a combinação de BIM e IA através de dados. Todavia, apontam a necessidade do desenvolvimento de linhas de pesquisas dedicadas a formalização do conhecimento do domínio de automação para potencial utilização dos dados BIM para aplicação de forma contextualizada em diferentes projetos da construção. As contribuições deste trabalho destacam a importância da exploração de novas tecnologias para o ambiente construído, ao passo que explana os desafios de incorporação na indústria. Esta pesquisa ainda contribui para a literatura através da identificação de potenciais tópicos a serem desenvolvidos que podem ser novas tendências de pesquisa.

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Biografia do Autor

Josivan Leite Alves, Universidade Federal do Pernambuco

Mestrado em Engenharia de Produção pela Universidade de São Paulo. Doutorando pela Universidade Federal de Pernambuco (Recife - PE, Brasil)

Rachel Perez Palha, Universidade Federal do Pernambuco

Doutorado em Engenharia de Produção. Professora Adjunto do curso de Engenharia de Civil da Univeridade Federal de Pernambuco (Recife - PE, Brasil)

Adiel Teixeira de Almeida Filho, Universidade Federal de Pernambuco

Doutorado em Engenharia de Produção. Professor Associado da Universidade Federal de Pernambuco (Recife - PE, Brasil).

Referências

ARIA, Massimo; CUCCURULLO, Corrado. bibliometrix : An R-tool for comprehensive science mapping analysis. Journal of Informetrics, [S. l.], v. 11, n. 4, p. 959–975, 2017. DOI: 10.1016/j.joi.2017.08.007. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S1751157717300500.

BOJE, Calin; GUERRIERO, Annie; KUBICKI, Sylvain; REZGUI, Yacine. Towards a semantic Construction Digital Twin: Directions for future research. Automation in Construction, [S. l.], v. 114, p. 103179, 2020. DOI: 10.1016/j.autcon.2020.103179. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S0926580519314785.

ÇETIN, Sultan; DE WOLF, Catherine; BOCKEN, Nancy. Circular Digital Built Environment: An Emerging Framework. Sustainability, [S. l.], v. 13, n. 11, p. 6348, 2021. DOI: 10.3390/su13116348. Disponível em: https://www.mdpi.com/2071-1050/13/11/6348.

COLLINS, Fiona C.; RINGSQUANDL, Martin; BRAUN, Alexander; HALL, Daniel M.; BORRMANN, Andre. Shape encoding for semantic healing of design models and knowledge transfer to scan-to-BIM. Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction, [S. l.], v. 175, n. 4, p. 160–180, 2022. DOI: 10.1680/jsmic.21.00032. Disponível em: https://www.icevirtuallibrary.com/doi/10.1680/jsmic.21.00032.

DARKO, Amos; CHAN, Albert P. C.; ADABRE, Michael A.; EDWARDS, David J.; HOSSEINI, M. Reza; AMEYAW, Ernest E. Artificial intelligence in the AEC industry: Scientometric analysis and visualization of research activities. Automation in Construction, [S. l.], v. 112, p. 103081, 2020. DOI: 10.1016/j.autcon.2020.103081. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S092658051930651X.

DOBRUCALI, Esra; DEMIRKESEN, Sevilay; SADIKOGLU, Emel; ZHANG, Chengyi; DAMCI, Atilla. Investigating the impact of emerging technologies on construction safety performance. Engineering, Construction and Architectural Management, [S. l.], 2022. DOI: 10.1108/ECAM-07-2022-0668. Disponível em: https://www.emerald.com/insight/content/doi/10.1108/ECAM-07-2022-0668/full/html.

DOUKARI, Omar; SECK, Boubacar; GREENWOOD, David. The Creation of Construction Schedules in 4D BIM: A Comparison of Conventional and Automated Approaches. Buildings, [S. l.], v. 12, n. 8, p. 1145, 2022. DOI: 10.3390/buildings12081145. Disponível em: https://www.mdpi.com/2075-5309/12/8/1145.

HETEMI, Ermal; ORDIERES-MERÉ, Joaquin; NUUR, Cali. An Institutional Approach to Digitalization in Sustainability-Oriented Infrastructure Projects: The Limits of the Building Information Model. Sustainability, [S. l.], v. 12, n. 9, p. 3893, 2020. DOI: 10.3390/su12093893. Disponível em: https://www.mdpi.com/2071-1050/12/9/3893.

IGWE, Uchenna Sampson; MOHAMED, Sarajul Fikri; AZWARIE, Mohd Bin Mat Dzahir; UGULU, Rex Asibuodu; AJAYI, Olusegun. Acceptance of contemporary technologies for cost management of construction projects. Journal of Information Technology in Construction, [S. l.], v. 27, p. 864–883, 2022. DOI: 10.36680/j.itcon.2022.042. Disponível em: https://www.itcon.org/paper/2022/42.

KIM, Kyungki; CHO, Yong; KIM, Kinam. BIM-Driven Automated Decision Support System for Safety Planning of Temporary Structures. Journal of Construction Engineering and Management, [S. l.], v. 144, n. 8, 2018. DOI: 10.1061/(ASCE)CO.1943-7862.0001519. Disponível em: https://ascelibrary.org/doi/10.1061/%28ASCE%29CO.1943-7862.0001519.

LEE, Seojoon; JEONG, Minkyeong; CHO, Chung-Suk; PARK, Jaewon; KWON, Soonwook. Deep Learning-Based PC Member Crack Detection and Quality Inspection Support Technology for the Precise Construction of OSC Projects. Applied Sciences, [S. l.], v. 12, n. 19, p. 9810, 2022. DOI: 10.3390/app12199810. Disponível em: https://www.mdpi.com/2076-3417/12/19/9810.

LEON-GARZA, Hugo; HAGRAS, Hani; PEÑA-RIOS, Anasol; CONWAY, Anthony; OWUSU, Gilbert. A type-2 fuzzy system-based approach for image data fusion to create building information models. Information Fusion, [S. l.], v. 88, p. 115–125, 2022. DOI: 10.1016/j.inffus.2022.07.007. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S1566253522000665.

LOPES, Ana Paula Vilas Boas Viveiros; DE CARVALHO, Marly Monteiro. Evolution of the open innovation paradigm: Towards a contingent conceptual model. Technological Forecasting and Social Change, [S. l.], v. 132, p. 284–298, 2018. DOI: 10.1016/j.techfore.2018.02.014. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S0040162518302786.

MARZOUK, Mohamed; ZAHER, Mohamed. Artificial intelligence exploitation in facility management using deep learning. Construction Innovation, [S. l.], v. 20, n. 4, p. 609–624, 2020. DOI: 10.1108/CI-12-2019-0138. Disponível em: https://www.emerald.com/insight/content/doi/10.1108/CI-12-2019-0138/full/html.

MIKALEF, Patrick; GUPTA, Manjul. Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, [S. l.], v. 58, n. 3, p. 103434, 2021. DOI: 10.1016/j.im.2021.103434. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S0378720621000082.

MOHANTA, Ashaprava; DAS, Sutapa. Decision support system for the early stage of green building envelope design considering energy and maintainability. Architectural Engineering and Design Management, [S. l.], v. 19, n. 2, p. 163–182, 2023. DOI: 10.1080/17452007.2022.2094869. Disponível em: https://www.tandfonline.com/doi/full/10.1080/17452007.2022.2094869.

MUSELLA, Christian; SERRA, Milena; MENNA, Costantino; ASPRONE, Domenico. Building information modeling and artificial intelligenc: Advanced technologies for the digitalisation of seismic damage in existing buildings. Structural Concrete, [S. l.], v. 22, n. 5, p. 2761–2774, 2021. DOI: 10.1002/suco.202000029. Disponível em: https://onlinelibrary.wiley.com/doi/10.1002/suco.202000029.

PAN, Yue; ZHANG, Limao. Roles of artificial intelligence in construction engineering and management: A critical review and future trends. Automation in Construction, [S. l.], v. 122, p. 103517, 2021. DOI: 10.1016/j.autcon.2020.103517. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S0926580520310979.

PEDRAL SAMPAIO, Rodrigo; AGUIAR COSTA, António; FLORES-COLEN, Inês. A Systematic Review of Artificial Intelligence Applied to Facility Management in the Building Information Modeling Context and Future Research Directions. Buildings, [S. l.], v. 12, n. 11, p. 1939, 2022. DOI: 10.3390/buildings12111939. Disponível em: https://www.mdpi.com/2075-5309/12/11/1939.

PETROVA, Ekaterina; PAUWELS, Pieter; SVIDT, Kjeld; JENSEN, Rasmus Lund. Towards data-driven sustainable design: decision support based on knowledge discovery in disparate building data. Architectural Engineering and Design Management, [S. l.], v. 15, n. 5, p. 334–356, 2019. DOI: 10.1080/17452007.2018.1530092. Disponível em: https://www.tandfonline.com/doi/full/10.1080/17452007.2018.1530092.

RODRIGUEZ-TREJO, Sergio; AHMAD, Ahmad Mohammad; HAFEEZ, Mian Atif; DAWOOD, Huda; VUKOVIC, Vladimir; KASSEM, Mohamad; NAJI, Khalid K.; DAWOOD, Nashwan. Hierarchy based information requirements for sustainable operations of buildings in Qatar. Sustainable Cities and Society, [S. l.], v. 32, p. 435–448, 2017. DOI: 10.1016/j.scs.2017.03.005. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S2210670716307119.

RŮŽIČKA, Jan; VESELKA, Jakub; RUDOVSKÝ, Zdeněk; VITÁSEK, Stanislav; HÁJEK, Petr. BIM and Automation in Complex Building Assessment. Sustainability, [S. l.], v. 14, n. 4, p. 2237, 2022. DOI: 10.3390/su14042237. Disponível em: https://www.mdpi.com/2071-1050/14/4/2237.

SACKS, Rafael; BRILAKIS, Ioannis; PIKAS, Ergo; XIE, Haiyan Sally; GIROLAMI, Mark. Construction with digital twin information systems. Data-Centric Engineering, [S. l.], v. 1, p. e14, 2020. DOI: 10.1017/dce.2020.16. Disponível em: https://www.cambridge.org/core/product/identifier/S2632673620000167/type/journal_article.

SANTOS, Paula de Oliveira; CARVALHO, Marly Monteiro De. Exploring the challenges and benefits for scaling agile project management to large projects: a review. Requirements Engineering, [S. l.], v. 27, n. 1, p. 117–134, 2021. DOI: 10.1007/s00766-021-00363-3. Disponível em: https://link.springer.com/10.1007/s00766-021-00363-3.

SHA, Huajing; XU, Peng; YANG, Zhiwei; CHEN, Yongbao; TANG, Jixu. Overview of computational intelligence for building energy system design. Renewable and Sustainable Energy Reviews, [S. l.], v. 108, p. 76–90, 2019. DOI: 10.1016/j.rser.2019.03.018. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S1364032119301510.

SHAHZAD, Muhammad; SHAFIQ, Muhammad Tariq; DOUGLAS, Dean; KASSEM, Mohamad. Digital Twins in Built Environments: An Investigation of the Characteristics, Applications, and Challenges. Buildings, [S. l.], v. 12, n. 2, p. 120, 2022. DOI: 10.3390/buildings12020120. Disponível em: https://www.mdpi.com/2075-5309/12/2/120.

SILVA, Tássia Farssura Lima; CARVALHO, Marly Monteiro; VIEIRA, Darli Rodrigues. BIM Critical-Success Factors in the Design Phase and Risk Management: Exploring Knowledge and Maturity Mediating Effect. Journal of Construction Engineering and Management, [S. l.], v. 148, n. 10, 2022. DOI: 10.1061/(ASCE)CO.1943-7862.0002343. Disponível em: https://ascelibrary.org/doi/10.1061/%28ASCE%29CO.1943-7862.0002343.

SOMAN, Ranjith K.; WHYTE, Jennifer K. Codification Challenges for Data Science in Construction. Journal of Construction Engineering and Management, [S. l.], v. 146, n. 7, 2020. DOI: 10.1061/(ASCE)CO.1943-7862.0001846. Disponível em: https://ascelibrary.org/doi/10.1061/%28ASCE%29CO.1943-7862.0001846.

TRANFIELD, David; DENYER, David; SMART, Palminder. Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. British Journal of Management, [S. l.], v. 14, n. 3, p. 207–222, 2003. DOI: 10.1111/1467-8551.00375. Disponível em: https://onlinelibrary.wiley.com/doi/10.1111/1467-8551.00375.

TURJO, Manoshi Das; KHAN, Mohammad Monirujjaman; KAUR, Manjit; ZAGUIA, Atef. Smart Supply Chain Management Using the Blockchain and Smart Contract. Scientific Programming, [S. l.], v. 2021, p. 1–12, 2021. DOI: 10.1155/2021/6092792. Disponível em: https://www.hindawi.com/journals/sp/2021/6092792/.

TURNER, Christopher J.; OYEKAN, John; STERGIOULAS, Lampros; GRIFFIN, David. Utilizing Industry 4.0 on the Construction Site: Challenges and Opportunities. IEEE Transactions on Industrial Informatics, [S. l.], v. 17, n. 2, p. 746–756, 2021. DOI: 10.1109/TII.2020.3002197. Disponível em: https://ieeexplore.ieee.org/document/9117064/.

WANG, Hongbo; HU, Yan. Artificial Intelligence Technology Based on Deep Learning in Building Construction Management System Modeling. Advances in Multimedia, [S. l.], v. 2022, p. 1–9, 2022. DOI: 10.1155/2022/5602842. Disponível em: https://www.hindawi.com/journals/am/2022/5602842/.

WANG, Hongxin; XU, Peng; SHA, Huajing; GU, Jiefan; XIAO, Tong; YANG, Yikun; ZHANG, Dingyi. BIM-based automated design for HVAC system of office buildings—An experimental study. Building Simulation, [S. l.], v. 15, n. 7, p. 1177–1192, 2022. DOI: 10.1007/s12273-021-0883-7. Disponível em: https://link.springer.com/10.1007/s12273-021-0883-7.

YANG, Yang; CHAN, Albert P. C.; SHAN, Ming; GAO, Ran; BAO, Fengyu; LYU, Sainan; ZHANG, Qingwen; GUAN, Junfeng. Opportunities and Challenges for Construction Health and Safety Technologies under the COVID-19 Pandemic in Chinese Construction Projects. International Journal of Environmental Research and Public Health, [S. l.], v. 18, n. 24, p. 13038, 2021. DOI: 10.3390/ijerph182413038. Disponível em: https://www.mdpi.com/1660-4601/18/24/13038.

ZHANG, Fan; CHAN, Albert P. C.; DARKO, Amos; CHEN, Zhengyi; LI, Dezhi. Integrated applications of building information modeling and artificial intelligence techniques in the AEC/FM industry. Automation in Construction, [S. l.], v. 139, p. 104289, 2022. DOI: 10.1016/j.autcon.2022.104289. Disponível em: https://linkinghub.elsevier.com/retrieve/pii/S0926580522001625.

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Publicado

29/10/2023

Como Citar

ALVES, J. L.; PALHA, R. P. .; ALMEIDA FILHO, A. T. de. Investigação das aplicações integradas de inteligência artificial e BIM na industria da construção civil. In: SIMPÓSIO BRASILEIRO DE TECNOLOGIA DA INFORMAÇÃO E COMUNICAÇÃO NA CONSTRUÇÃO, 4., 2023. Anais [...]. Porto Alegre: ANTAC, 2023. p. 1–12. DOI: 10.46421/sbtic.v4i00.2409. Disponível em: https://eventos.antac.org.br/index.php/sbtic/article/view/2409. Acesso em: 6 maio. 2024.

Edição

Seção

Indústria 4.0 e 5.0 no projeto e operação de empreemdimentos

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