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Current Research Directions on the Application of Artificial Intelligence in Construction in the Context of Occupational Safety

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Aktualne kierunki badań nad zastosowaniem sztucznej inteligencji w budownictwie w kontekście bezpieczeństwa pracy
Języki publikacji
EN PL
Abstrakty
EN
The aim of the research was to investigate the current possibilities of using artificial intelligence (AI) in processes related to occupational safety in construction. Previous research on the use of AI in the construction sector has shown the high effectiveness of these methods, including: big data analysis, training and education. The implementation of AI in construction can significantly improve occupational safety. However, it is necessary to take into account ethical aspects and develop appropriate legal regulations.
PL
Celem badań było zbadanie aktualnych możliwości zastosowania sztucznej inteligencji (AI) w procesach związanych z bezpieczeństwem pracy w budownictwie. Dotychczasowe badania dotyczące zastosowania AI w sektorze budownictwa wykazały dużą skuteczność tych metod m.in. w analizie dużych zbiorów danych, szkoleniach i edukacji. Wdrożenie AI w budownictwie może znacznie poprawić bezpieczeństwo pracy. Konieczne jest jednak uwzględnienie aspektów etycznych oraz opracowanie odpowiednich regulacji prawnych.
Rocznik
Tom
Strony
18--25
Opis fizyczny
Bibliogr. 29 poz., il.
Twórcy
  • Politechnika Wrocławska, Wydział Budownictwa Lądowego i Wodnego
  • Politechnika Wrocławska, Wydział Budownictwa Lądowego i Wodnego
Bibliografia
  • [1] Samovia J. “Facts On Safety At Work. International Labour Organization”, 2021.
  • [2] Usama M., Ullah U., Muhammad Z., Islam T., Hashmi S.S. “AI-enabled risk assessment and safety management in construction”, Ethical Artificial Intelligence in Power Electronics, pp. 105-132, 2024, eBook ISBN: 9781032648323
  • [3] Kamal I.S.M., Ahmad I.N., Ma’arof M.I.N. “Review on Accidents Related to Human Factors at Construction Site”, Advanced Engineering Forum, vol. 10, pp. 154-159, 2013, DOI: 10.4028/www.scientific.net/aef.10.154.
  • [4] Woźniak Z., Hoła B., Ciszewski J., Stelmaszczyk M. “Significance of near misses for work safety in construction”, Przegląd Budowlany. 2022, vol. 9/10, s. 90-93.
  • [5] Woźniak Z., Hoła B., Ciszewski J., Stelmaszczyk M., “Accident prevention index based on the number of dangerous events in a Polish construction company”, Przegląd Budowlany, vol. R. 94, nr, no. 9-10, pp. 184-189, 2023, DOI: 10.5604/01.3001.0053.9396.
  • [6] “GUS – Bank Danych Lokalnych.” Accessed: May 06, 2024. [Online]. Available: https://bdl.stat.gov.pl/bdl/start
  • [7] Woźniak Z. and Hoła B., “The structure of near misses and occupational accidents in the polish construction industry”, Heliyon, vol. 10, no. 4, 2024, DOI: 10.1016/J.HELIYON.2024.E26410.
  • [8] Sultanov R., Sulaiman S., Li H., Meshcheryakov R., Magid E. “A Review on Collaborative Robots in Industrial and Service Sectors”, 2022 International Siberian Conference on Control and Communications, SIBCON 2022 – Proceedings, 2022, DOI: 10.1109/SIBCON56144.2022.10003014.
  • [9] Chen S., Zheng Y., Cattani C., Wang W. “Modeling of Biological Intelligence for SCM System Optimization”, Comput Math Methods Med, vol. 2012, no. 1, p. 769702, 2012, DOI: 10.1155/2012/769702.
  • [10] Lu P., Chen S., and Zheng Y. “Artificial Intelligence in Civil Engineering”, Math Probl Eng, vol. 2012, no. 1, p. 145974, 2012, DOI: 10.1155/2012/145974.
  • [11] “Classification if the educational texts styles with the methods of artificial intelligence”, Journal of Baltic Science Education, vol. 16, no. 3, pp. 324-336, 2017.
  • [12] Butler-Adam J. “The Fourth Industrial Revolution and education”, South African Journal of Science, vol. 114, no. 5-6, pp. 1-1, 2018, DOI: 10.17159/ SAJS.2018/A0271.
  • [13] Walicka M., Czemiel-Grzybowska W. “Artificial intelligence and working capital management in the prism of Industry 5.0”, Management Academy, vol. 7, no. 4, p. 2023, DOI: 10.24427/AZ-2023-0058.
  • [14] Jeelani I., Ramshankar H., Han K., Albert A., Asadi K. “Real-Time Hazard Proximity Detection-Localization of Workers Using Visual Data”, Computing in Civil Engineering 2019: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019, pp. 281-289, 2019, DOI: 10.1061/9780784482438.036.
  • [15] Chen H., Mao Y., Xu Y., Wang R. “The Impact of Wearable Devices on the Construction Safety of Building Workers: A Systematic Review”, Sustainability (Switzerland), vol. 15, no. 14, p. 11165, 2023, DOI: 10.3390/ SU151411165/S1.
  • [16] Sardinha L., Baleiras J.V., Sousa S., Lima T.M., Gaspar P.D. “Decision Support System (DSS) for Improving Production Ergonomics in the Construction Sector”, Processes 2024, Vol. 12, Page 2503, vol. 12, no. 11, p. 2503, 2024, DOI: 10.3390/PR12112503.
  • [17] Rabbi A.B.K., Jeelani I. “AI integration in construction safety: Current state, challenges, and future opportunities in text, vision, and audio based applications”, Autom Constr, vol. 164, p. 105443, 2024, DOI: 10.1016/j.autcon. 2024.105443.
  • [18] Kisaezehra, M.U. Farooq, M. A. Bhutto, A. K. Kazi, “Real-Time Safety Helmet Detection Using Yolov5 at Construction Sites”, Intelligent Automation and Soft Computing, vol. 36, no. 1, pp. 911-927, 2023, DOI: 10.32604/ iasc.2023.031359.
  • [19] Shanti M.Z. et al., “A Novel Implementation of an AI-Based Smart Construction Safety Inspection Protocol in the UAE”, IEEE Access, vol. 9, pp. 166603-166616, 2021, DOI: 10.1109/ACCESS.2021.3135662.
  • [20] Pandithawatta S., Ahn S., Rameezdeen R., Chow C.W.K., Gorjian N. “Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident Prevention”, Buildings, vol. 14, no. 11, 2024, DOI: 10.3390/buildings14113403.
  • [21] Koc K., Ekmekcioğlu Ö., Gurgun A.P. “Accident prediction in construction using hybrid wavelet-machine learning”, Autom Constr, vol. 133, p. 103987, 2022, DOI: 10.1016/j.autcon.2021.103987.
  • [22] Klempous R., Kluwak K., Idzikowski R., Nowobilski T., Zamojski T. “Possibility analysis of danger factors visualization in the construction environment based on Virtual Reality model”, 8th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2017 - Proceedings, vol. 2018-January, 2017, DOI: 10.1109/COGINFOCOM.2017.8268271.
  • [23] Jacobsen E.L., Solberg A., Golovina O., Teizer J. “Active personalized construction safety training using run-time data collection in physical and virtual reality work environments”, Construction Innovation, vol. 22, no. 3, pp. 531-553, 2022, DOI: 10.1108/CI-06-2021-0113/FULL/PDF.
  • [24] Uddin S.M.J., Albert A., Ovid A., Alsharef A. “Leveraging ChatGPT to Aid Construction Hazard Recognition and Support Safety Education and Training”, Sustainability 2023, Vol. 15, Page 7121, vol. 15, no. 9, p. 7121, 2023, DOI: 10.3390/SU15097121.
  • [25] Getuli V. et al., “Agent-based simulation framework for enhanced construction site risk estimation and safety management“, Journal of Information Technology in Construction (ITcon), vol. 29, 2024, DOI: 10.36680/j.itcon. 2024.054.
  • [26] Szruba M. “Modern technologies and innovations are changing construction”, Technologies and innovations in construction.
  • [27] Kaczorek K. “Possibilities of implementing the Construction 4.0 concept in the area of occupational health and safety”, Przegląd Budowlany, vol. 94, no. 9-10, pp. 105-109, 2023, DOI: 10.5604/01.3001.0053.9372.
  • [28] Ho K., Tang D. “Artificial Intelligence in Occupational Health and Safety Risk Management of Construction, Mining, and Oil and Gas Sectors: Advances and Prospects”, Journal of Engineering Research and Reports, vol. 26, no. 6, pp. 241-253, 2024, DOI: 10.9734/JERR/2024/V26I61177.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-16e8d915-b56b-45ee-9ab7-b3e83b913563
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