Abstract
In the civil engineering supervision, the management processes about personnel, materials, quality, safety, schedule and etc. are complex, which include large amount of data, involve more participants, and timely coordination and feedback is difficult. In this paper, we propose the data integration idea based on data-driven, which could guide the whole life cycle of civil engineering supervision from the top-level data organization, supervision of business processes, the interactive units and the users, the four-elements method TDTM and so on. Then, the data integration algorithms of civil engineering supervision are put forward to integrate the civil engineering supervision data from outside to inside and from coarse-grained to fine-grained, eliminate contradictions and redundancy and ensure data consistency. Finally, the civil engineering supervision data entities are determined, and we further analyze and discuss its query and report, data maintenance and conversion, and compare the functions in the different supervision platform. The civil engineering supervision unified data platform proposed could maintain the independence of the data, have the good scalability and support the more functions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Li, X.: Research and application of quality management in engineering supervision. Industry C 04, 00044–00045 (2016)
Li, X., Xu, J., Zhang, Q.: Research on construction schedule management based on BIM technology. Procedia Eng. 174, 657–667 (2017)
Wang, K.C., Wang, W.C., Wang, H.H., et al.: Applying building information modeling to integrate schedule and cost for establishing construction progress curves. Autom. Constr. 72, 397–410 (2016)
Faghihi, V., Reinschmidt, K.F., Kang, J.H.: Construction scheduling using genetic algorithm based on building information model. Expert Syst. Appl. 41(16), 7565–7578 (2014)
Hardison, D., Behm, M., Hallowell, M.R., et al.: Identifying construction supervisor competencies for effective site safety. Saf. Sci. 65, 45–53 (2014)
Zhang, S., Boukamp, F., Teizer, J.: Ontology-based semantic modeling of construction safety knowledge: towards automated safety directioning for job hazard analysis (JHA). Autom. Constr. 52, 29–41 (2015)
Gurcanli, G.E., Bilir, S., Sevim, M.: Project based risk assessment and safety cost estimation for residential building construction projects. Saf. Sci. 80, 1–12 (2015)
Ganah, A., John, G.A.: Integrating building information modeling and health and safety for onsite construction. Saf. Health Work 6(1), 39–45 (2015)
Jiao, Y., Wang, Y., Zhang, S., et al.: A cloud approach to unified lifecycle data management in architecture, engineering, construction and facilities management: integrating BIMs and SNS. Adv. Eng. Inf. 27, 173–188 (2013)
Alreshidi, E., Mourshed, M., Rezgui, Y.: Factors for effective BIM governance. J. Build. Eng. 10, 89–101 (2017)
Chien, S., Chuang, T., Yu, H.S., et al.: Implementation of cloud BIM-based platform towards high-performance building services. Procedia Environ. Sci. 38, 436–444 (2017)
Fröbel, T., Firmenich, B., Koch, C.: Quality assessment of coupled civil engineering applications. Adv. Eng. Inf. 25(4), 625–639 (2011)
Lou, J., Xu, J., Wang, K.: Study on construction quality control of urban complex project based on BIM. Procedia Eng. 174, 668–676 (2017)
Chen, L.J., Luo, H.: A BIM-based construction quality management model and its applications. Autom. Constr. 46, 64–73 (2014)
Niknam, M., Karshenas, S.: A shared ontology approach to semantic representation of BIM data. Autom. Constr. 80, 22–36 (2017)
Opitz, F., Windisch, R., Scherer, R.J.: Integration of document-and model-based building information for project management support. Procedia Eng. 85, 403–411 (2014)
Lee, Y.C., Eastman, C.M., Solihin, W.: An ontology-based approach for developing data exchange requirements and model views of building information modeling. Adv. Eng. Inf. 30(3), 354–367 (2016)
Li, H., Wang, Y.: BIM-based project management and management system. China Civ. Eng. Manag. J. 33(6), 78–82 (2016)
Shaker, H.R., Lazarova-Molnar, S.: A new data-driven controllability measure with application in intelligent buildings. Energy Build. 138, 526–529 (2017)
Wang, H., Zhang, T., Wang, J., et al.: Research on data-driven method for TOD period identification of regional traffic. J. Wuhan Univ. Technol. (Transp. Sci. Eng.) 38(1), 40–45 (2014)
Wen, C., Lu, F., Bao, Z., et al.: A summary of data-driven micro fault diagnosis methods. Acta Autom. Sin. 42(9), 1285–1299 (2016)
Erlingsson, U.: Data-driven software security: models and methods. In: Proceedings of 2016 IEEE 29th Computer Security Foundations Symposium (CSF), pp. 9–15 (2016)
Jiang, J., Sekar, V., Stoica I., et al.: Unleashing the potential of data-driven networking. In: Proceedings of 9th International Conference on COMmunication Systems & NETworkS (COMSNET) (2017)
Pinelli, F., Nair, R., Calabrese, F., et al.: Data-driven transit network design from mobile phone trajectories. IEEE Trans. Intell. Transp. Syst. 17(6), 1724–1733 (2016)
Acknowledgements
This work was supported in part by the National Natural Science Fund of China under grant 61003130, in part by the Sub research topic of a National Science and Technology Support Plan under Grant 2012BAH33F03, and in part by The Natural Science Foundation of Hubei Province, China under Grant 2015CFB525.
Author information
Authors and Affiliations
Corresponding authors
Appendix
Rights and permissions
About this article
Cite this article
Wu, S., Song, H., Li, T. et al. Integration and formal representation in civil engineering supervision based on data-driven. Cluster Comput 22 (Suppl 3), 6499–6516 (2019). https://doi.org/10.1007/s10586-018-2277-x
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10586-018-2277-x