Aplicações de BIM, RPA e visão computacional de forma integrada para o planejamento e controle da segurança em canteiros de obras

Hugo Sefrian Peinado; Dayana Bastos Costa

doi:10.46421/sibragec.v13i00.2604

Aplicações de BIM, RPA e visão computacional de forma integrada para o planejamento e controle da segurança em canteiros de obras

Autores

Hugo Sefrian Peinado Universidade Federal da Bahia https://orcid.org/0000-0001-7868-0219 http://lattes.cnpq.br/1591975944797856
Dayana Bastos Costa Universidade Federal da Bahia https://orcid.org/0000-0002-1457-6401 http://lattes.cnpq.br/5523401011280282

DOI:

https://doi.org/10.46421/sibragec.v13i00.2604

Palavras-chave:

Construção 4.0, Drone, Aprendizado de Máquina, Modelagem da Informação da Construção, Revisão Sistemática de literatura

Resumo

Há diversas aplicações de tecnologias digitais associadas ao paradigma da Construção 4.0 no contexto da segurança. No entanto, as implementações ocorrem muitas vezes de forma individual, não sendo aproveitado o potencial de aplicação integrada dessas tecnologias. Nesse sentido, esse artigo tem como objetivo analisar as aplicações integradas de modelagem da informação da construção (BIM), aeronaves remotamente pilotadas (RPA) e visão computação (VC) no planejamento e controle da segurança (PCS) em canteiros de obras. A estratégia metodológica adotada foi a Revisão Sistemática de Literatura. A partir dos 14 estudos considerados elegíveis, foram identificados modelos, métodos e frameworks que tratam da implementação de BIM, RPA e VC em duplas ou trio destinadas ao PCS. As contribuições observadas dão indícios do potencial de uso dessas tecnologias integradas aplicadas ao PCS. No entanto, considerando o estágio inicial de amadurecimento de propostas de integração envolvendo as tecnologias, sugere-se o desenvolvimento de modelos/frameworks validados mais robustos que integrem BIM, RPA e VC aproveitando as potencialidades individuais dessas tecnologias.

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Biografia do Autor

Hugo Sefrian Peinado, Universidade Federal da Bahia

Mestrado em Engenharia Urbana pela Universidade Estadual de Maringá (Maringá - PR, Brasil). Doutorando em Engenharia Civil pela Universidade Federal da Bahia (Salvador - BA, Brasil).

Dayana Bastos Costa, Universidade Federal da Bahia

Doutorado em Engenharia Civil pela Universidade Federal do Rio Grande do Sul (Porto Alegre - RS, Brasil). Professora Associada do Departamento de Construção e Estruturas da Universidade Federal da Bahia (Salvador - BA, Brasil)

Referências

ALIZADEHSALEHI, S.; ASNAFI, M.; YITMEN, I.; CELIK, T. UAS-BIM based Real-time Hazard Identification and Safety Monitoring of Construction Projects. In: Nordic Conference on Construction Economics and Organization, 9, 2017. Anais [...], 2017.

ALIZADEHSALEHI, S.; YITMEN, I.; CELIK, T.; ARDITI, D. The effectiveness of an integrated BIM/UAV model in managing safety on construction sites. International Journal of Occupational Safety and Ergonomics, vol. 26, no. 4, p. 829–844, 1 Oct. 2020. https://doi.org/10.1080/10803548.2018.1504487.

ASADZADEH, A.; ARASHPOUR, M.; LI, H.; NGO, T.; BAB-HADIASHAR, A.; RASHIDI, A. Sensor-based safety management. Automation in Construction, vol. 113, 1 May 2020. https://doi.org/10.1016/j.autcon.2020.103128.

AWOLUSI, I.; AKINSEMOYIN, A.; CHAKRABORTY, D.; AL-BAYATI, A. Worker Safety and Health Activity Monitoring in Construction Using Unmanned Aerial Vehicles and Deep Learning. 2022. In: Construction Research Congress 2022, 2022. Anais [...]. 2022. p. 463–473.

BADUGE, S. K.; THILAKARATHNA, S.; PERERA, J. S.; ARASHPOUR, M.; SHARAFI, P.; TEODOSIO, B.; SHRINGI, A.; MENDIS, P. Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications. Automation in Construction, vol. 141, 1 Sep. 2022. https://doi.org/10.1016/j.autcon.2022.104440.

CHOE, S.; LEITE, F. Construction safety planning: Site-specific temporal and spatial information integration. Automation in Construction, vol. 84, p. 335–344, 1 Dec. 2017. https://doi.org/10.1016/j.autcon.2017.09.007.

COSTA, D.B.; GHEISARI, M.; ALARCÓN, L.F. UAS applications to support Lean Construction implementarion. In: GONZÁLEZ, V. A.; HAMZEH, F.; ALARCÓN, L.F. (Eds.) Lean Construction 4.0: Driving a Digital Revolution of Production Management in the AEC Industry. New York: Routledge, 2023.

DOBRUCALI, E.; SADIKOGLU, E.; DEMIRKESEN, S.; ZHANG, C.; TEZEL, A.; KIRAL, I. A. A bibliometric analysis of digital technologies use in construction health and safety. Engineering, Construction and Architectural Management, 20 Mar. 2023. https://doi.org/10.1108/ecam-08-2022-0798.

DRESH, A. LACERDA, D.P.; ANTUNES JR., J.A.V. Design Science Research: a Method for Science and Technology Advances. Springer, 2015.

GHEISARI, M.; RASHIDI, A.; ESMAEILI, B. Using Unmanned Aerial Systems for Automated Fall Hazard Monitoring. 2018. In: Construction Research Congress 2018, 2018. Anais [...] 2018. p. 62–2.

GUO, H.; YU, Y.; SKITMORE, M. Visualization technology-based construction safety management: A review. Automation in Construction, vol. 73, p. 135–144, 1 Jan. 2017. https://doi.org/10.1016/j.autcon.2016.10.004.

GUO, Y.; NIU, H.; LI, S. Safety Monitoring in Construction Site based on Unmanned Aerial Vehicle Platform with Computer Vision using Transfer Learning Techniques. 2018. In: Asia-Pacific Workshop on Structural Health Monitoring, 7, 2018. Anais [...] 2018. p. 1–9. Available at: http://www.ndt.net/?id=24114.

JOHANSEN, K.; FIGUEIREDO, R.; GOLOVINA, O.; TEIZER, J.. Autonomous Safety Barrier Inspection in Construction: An Approach Using Unmanned Aerial Vehicles and SafeBIM. International Symposium on Automation and Robotics in Construction (ISARC 2021), 38, 2021. Anais [...] 2021. p. 629–636.

KOLAR, Z.; CHEN, H.; LUO, X. Transfer learning and deep convolutional neural networks for safety guardrail detection in 2D images. Automation in Construction, vol. 89, p. 58–70, 1 May 2018. https://doi.org/10.1016/j.autcon.2018.01.003.

LIMA, M. I. S. C.; COSTA, D. B. Recomendações e boas práticas para a integração do monitoramento da segurança com drone ao planejamento e controle da segurança de obras. Ambiente Construído, vol. 23, no. 1, p. 213–231, Jan. 2023. https://doi.org/10.1590/s1678-86212023000100659.

LI, Y.; ESMAEILI, B.; GHEISARI, M.; KOSECKA, J.; RASHIDI, A. Using Unmanned Aerial Systems (UAS) for Assessing and Monitoring Fall Hazard Prevention Systems in High-rise Building Projects. arXiv, 2022. https://doi.org/10.3390/xxxxx.

LIBERATI, A.; ALTMAN, D.G.; TETZLAFF, J.; MULROW, C.; GOTZSCHE, P.C.; IOANNIDIS, J.P.A.; CLARKE,M; DEVEREAUX, P.J.; KLEIJNEN, J; MOHER, D. The PRISMA statement for reporting systematic reviews and meta- analyses of studies that evaluate health care interventions: explanation and elaboration. Journal of clinical epidemiology, v. 62 (10), p.1-34, 2009.

MANZOOR, B.; OTHMAN, I.; POMARES, J. C.; CHONG, H. Y. A research framework of mitigating construction accidents in high-rise building projects via integrating building information modeling with emerging digital technologies. Applied Sciences (Switzerland), vol. 11, no. 18, 1 Sep. 2021. https://doi.org/10.3390/app11188359.

MARTÍNEZ-AIRES, M. D.; LÓPEZ-ALONSO, M.; MARTÍNEZ-ROJAS, M. Building information modeling and safety management: A systematic review. Safety Science, vol. 101, p. 11–18, 1 Jan. 2018. https://doi.org/10.1016/j.ssci.2017.08.015.

MARTINEZ, J. G.; GHEISARI, M.; ALARCÓN, L. F. UAV Integration in Current Construction Safety Planning and Monitoring Processes: Case Study of a High-Rise Building Construction Project in Chile. Journal of Management in Engineering, vol. 36, no. 3, May 2020. https://doi.org/10.1061/(asce)me.1943-5479.0000761.

MELO, R. R. S.; COSTA, D. B. Integrating resilience engineering and UAS technology into construction safety planning and control. Engineering, Construction and Architectural Management, vol. 26, no. 11, p. 2705–2722, 5 Nov. 2019. https://doi.org/10.1108/ECAM-12-2018-0541.

MELO, R. R. S.; COSTA, D. B.; ÁLVARES, J. S.; IRIZARRY, J. Applicability of unmanned aerial system (UAS) for safety inspection on construction sites. Safety Science, vol. 98, p. 174–185, 1 Oct. 2017. https://doi.org/10.1016/j.ssci.2017.06.008.

OTTONI, A. L C; NOVO, M. S; COSTA, D. B. Deep Learning for Vision Systems in Construction 4.0: A Systematic Review. Signal, image and video processing, 2022. Available at: http://www.scopus.com.

PANERU, S.; JEELANI, I. Computer vision applications in construction: Current state, opportunities & challenges. Automation in Construction, vol. 132, 1 Dec. 2021. https://doi.org/10.1016/j.autcon.2021.103940.

PEINADO, H.S.; MELO, R.R.S.; SANTOS, M.C.F; COSTA, D.B. Potential application of Deep Learning and UAS for guardrail safety inspections. Annual Conference of the International Group for Lean Construction, 31., 2023, Lille. Anais […] IGLC, 2023.

PHAM, H. T.T.L.; RAFIEIZONOOZ, M.; HAN, S.; LEE, D. E. Current status and future directions of deep learning applications for safety management in construction. Sustainability (Switzerland), vol. 13, no. 24, 1 Dec. 2021. https://doi.org/10.3390/su132413579.

PRISMA. PRISMA 2020 flow diagram for new systematic reviews which included searches of databases and registers only, 2020. Disponível em: https://prisma-statement.org//PRISMAStatement/FlowDiagram Acesso em: 02 fev. 2023.

REY, R. O.; MELO, R. R. S.; COSTA, D. B. Design and implementation of a computerized safety inspection system for construction sites using UAS and digital checklists – Smart Inspecs. Safety Science, vol. 143, 1 Nov. 2021. https://doi.org/10.1016/j.ssci.2021.105430.

SACKS, R.; EASTMAN, C.; LEE, G.; TEICHOLZ, P. BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers, Contractors, and Facility Managers. Hoboken: Wiley, 2018.

SHANTI, M. Z.; CHO, C. S.; DE SOTO, B. G.; BYON, Y. J.; YEUN, C. Y.; KIM, T. Y. Real-time monitoring of work-at-height safety hazards in construction sites using drones and deep learning. Journal of Safety Research, vol. 83, p. 364–370, 1 Dec. 2022. https://doi.org/10.1016/j.jsr.2022.09.011.

SHARMA, S.; VENKATA SUSMITHA, A. V.; VAN, L. D.; TSENG, Y. C. An Edge-Controlled Outdoor Autonomous UAV for Colorwise Safety Helmet Detection and Counting of Workers in Construction Sites. In: IEEE Vehicular Technology Conference, 2021. Anais [...] Institute of Electrical and Electronics Engineers Inc., 2021 https://doi.org/10.1109/VTC2021-Fall52928.2021.9625393.

TRAN, S. V.-T.; NGUYEN, T. L.; PARK, C. A BIM Integrated Hazardous Zone Registration Using Image Stitching. 2021. In: International Symposium on Automation and Robotics in Construction (ISARC2021), 38, 2021. Anais [...]. 2021. p. 176–181.

WANG, K.; GUO, F.; ZHANG, C.; SCHAEFER, D. From Industry 4.0 to Construction 4.0: barriers to the digital transformation of engineering and construction sectors. Engineering, Construction and Architectural Management, 2022. https://doi.org/10.1108/ECAM-05-2022-0383.

YANG, B.; ZHANG, B.; ZHANG, Q.; WANG, Z.; DONG, M.; FANG, T. Automatic detection of falling hazard from surveillance videos based on computer vision and building information modeling. Structure and Infrastructure Engineering, vol. 18, no. 7, p. 1049–1063, 2022. https://doi.org/10.1080/15732479.2022.2039217.

YAN, G.; SUN, Q.; HUANG, J.; CHEN, Y. Helmet detection based on deep learning and random forest on UAV for power construction safety. Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 25, no. 1, p. 40–49, 20 Jan. 2021. https://doi.org/10.20965/JACIII.2021.P0040.

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Publicado

2023-11-05

Como Citar

PEINADO, Hugo Sefrian; COSTA, Dayana Bastos. Aplicações de BIM, RPA e visão computacional de forma integrada para o planejamento e controle da segurança em canteiros de obras. In: SIMPÓSIO BRASILEIRO DE GESTÃO E ECONOMIA DA CONSTRUÇÃO, 13., 2023. Anais [...]. Porto Alegre: ANTAC, 2023. p. 1–9. DOI: 10.46421/sibragec.v13i00.2604. Disponível em: https://eventos.antac.org.br/index.php/sibragec/article/view/2604. Acesso em: 23 nov. 2024.