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The BIMbot: A Cognitive Assistant in the BIM Room

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Abstract

Today, collaborative environment method is of with widespread use among project stakeholders. They benefit project planning in a variety of ways, including by enabling team members to build stronger relationships, enhance communication, and perform efficient planning, to name several. The collaboration occurs in sessions that immerse stakeholders in an environment commonly referred to as a BIM room —a shared space that enables project stakeholders, such as architects, general contractors, structural and MEP trades, and other specialized knowledge actors, to physically or virtually meet and to establish constant presence. The BIM room is a medium for stakeholders (BIM-room participants) to more accurately and efficiently make informed decisions on end to end construction problems. This project is aimed at investigating the use of information technology as a mediating mechanism to facilitate sharing meanings of expressions and to assist stakeholders in effectively finding relevant information that connects to their intent in the BIM-room. This research proposes the creation and implementation of a cognitive assistant to project stakeholders: BIMbot. The BIMbot is an agent that will have the ability to simulate a conversation or a messaging exchange with a present actor. From the actor-BIM-bot exchange and having an order, command, or request, BIMbot will carry common functions for the actors within the BIM room like retrieve the current version of family-objects of the BIM; load, filter, and view section(s) of interest; automate object placement; etc. BIMbot is designed to produce significantly more efficient interaction of collaborative meetings in the BIM room.

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References

  1. Anon, (n.d.). What is BIM?/NBS. [online] Available at: https://www.thenbs.com/knowledge/what-is-building-information-modelling-bim. Accessed 2018

  2. Dossick, C.S., Anderson, A., Azari, R., Iorio, J., Neff, G., Taylor, J.E.: Messy talk in virtual teams: achieving knowledge synthesis through shared visualizations. J. Manag. Eng. 31(1), A4014003 (2015)

    Article  Google Scholar 

  3. Dossick, C., Neff, G.: Messy talk and clean technology: communication, problem solving and collaboration using building information modelling. Eng. Proj. Organ. J. 1(2), 83–93 (2011)

    Article  Google Scholar 

  4. Merschbrock, C., ErikMunkvold, B.: Effective digital collaboration in the construction industry—A case study of BIM deployment in a hospital construction project (2018)

    Google Scholar 

  5. Addor, M., Santos, E.: BIM design coordination room infrastructure: assessment of communication activities. In: Computing in Civil and Building Engineering (2014), (2018)

    Google Scholar 

  6. Georgia Tech BIM Requirements and Guidelines for Architects, Engineers and Contractors., 1st ed., pp. 1–39. Atlanta, Georgia Institute of Technology (2011)

    Google Scholar 

  7. Jack, C.: CHATBOT: Architecture, Design, and Development (2017)

    Google Scholar 

  8. Vinyals, O., Quoc, V. Le.: A Neural Conversational Model (2015)

    Google Scholar 

  9. Alom, M.Z., Taha, T.M., Yakopcic, C., Westberg, S., Hasan, M., Van Esesn, B.C., Awwal, A.A.S., Asari, V.K. :The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches (2018)

    Google Scholar 

  10. Wu, Y., Schuster, M., Chen, Z., Le, Q.V., Norouzi, M. : Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation (2016)

    Google Scholar 

  11. Sutskever, I., Vinyals, O., Le, Q.V.: Sequence to Sequence Learning with Neural Networks (2014)

    Google Scholar 

  12. Cho, K., Merrienboer, B.V., Bahdanau, D., Bengio, Y. : On the properties of neural machine translation: encoder-decoder approaches. Comp. Sci. (2014a)

    Google Scholar 

  13. Google’s NMT Documentation—https://github.com/tensorflow/nmt

  14. Lipton, Z.C., Berkowitz, J., Elkan, C.: A Critical Review of Recurrent Neural Networks for Sequence Learning (2015)

    Google Scholar 

  15. Karpathy, A. : The Unreasonable Effectiveness of Recurrent Neural Networks. http://karpathy.github.io/2015/05/21/rnn-effectiveness/

  16. Ramamoorthy, S.: Chatbots with Seq2Seq. Retrieved from http://suriyadeepan.github.io/2016-06-28-easy-seq2seq/

  17. Bahdanau, D., Cho, K., Bengio, Y.: Neural Machine Translation by Jointly Learning to Align and Translate (2014)

    Google Scholar 

  18. Sennrich, R., Haddow, B., Birch, A.: Neural Machine Translation of Rare Words with Subword Units (2016)

    Google Scholar 

  19. Veizenbaum, J.: ELIZA—A Computer Program For the Study of Natural Language Communication Between Man And Machine (1966)

    Google Scholar 

  20. Bird, S., Klein, E., Loper, E. : Analyzing text with Natural Language Toolkit

    Google Scholar 

  21. Liu, F., Lu, H., Neubig, G. : Handling Homographs in Neural Machine Translation (2018)

    Google Scholar 

  22. Yoon, S., Kim, S., Choi, J., Keum, D., Jo, C.: A proposal for using BIM model created in design to construction phase—Case Study on preconstruction adopting BIM. J. KIBIM 5(4), 1–10 (2015)

    Article  Google Scholar 

  23. Shafiq, M., Matthews, J., Lockley, S. : A study of BIM collaboration requirements and available features in existing model collaboration systems. In: International Council for Research and Innovation in Building and Construction (2013)

    Google Scholar 

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Correspondence to Ivan Mutis .

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Mutis, I., Ramachandran, A., Martinez, M.G. (2019). The BIMbot: A Cognitive Assistant in the BIM Room. In: Mutis, I., Hartmann, T. (eds) Advances in Informatics and Computing in Civil and Construction Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-00220-6_19

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  • DOI: https://doi.org/10.1007/978-3-030-00220-6_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00219-0

  • Online ISBN: 978-3-030-00220-6

  • eBook Packages: EngineeringEngineering (R0)

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