BIM-based space management system for operation and maintenance phase in educational office buildings

    Guofeng Ma Affiliation
    ; Xue Song Affiliation
    ; Shanshan Shang Affiliation


Lists and floor plans have been widely adopted as space management tools for educational office buildings. However, the two-dimensional floor plans fail to present the indoor complexity, which hinders users from intuitively observing the indoor equipment arrangements and adapting to the indoor environment within a short time. Meanwhile, insufficient research has been conducted on space management tools regarding building indoor navigation. A Building Information Modeling Space Management (BIMSM) system was proposed in this study based on BIM. This system is comprised of two components, i.e. indoor space allocation management and indoor path navigation. The real-time space usage can be queried and user demands may be matched with available space by applying the Space Usage Analysis (SUA) theory. After the establishment of indoor maps, an improved A* algorithm is used to provide smooth navigation paths, and the visualization of such paths can be provided in mobile terminals. The BIMSM system was applied in an office building in a university in Shanghai, China. In this case study, the overall user satisfaction reached 91.6% by greatly reducing space arrangement failures. The time indoor navigation took outperformed that based on the traditional A* algorithm, with the search efficiency increasing 5.28%.

First published online 17 December 2019

Keyword : building information modeling (BIM), space management (SM), space usage analysis (SUA), visualization, A* algorithm, indoor navigation

How to Cite
Ma, G., Song, X., & Shang, S. (2020). BIM-based space management system for operation and maintenance phase in educational office buildings. Journal of Civil Engineering and Management, 26(1), 29-42.
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Jan 6, 2020
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Abdullah, S., Ali, H. M., & Sipan, I. (2012). Benchmarking space usage in higher education institutes: attaining efficient use. Journal of Techno-Social, 4(1), 11-20.

Atazadeh, B., Kalantari, M., Rajabifard, A., Ho, S., & Champion, T. (2017). Extending a BIM-based data model to support 3D digital management of complex ownership spaces. International Journal of Geographical Information Science, 31(3), 499522.

Becerik-Gerber, B., Jazizadeh, F., Li, N., & Calis, G. (2011). Application areas and data requirements for BIM-enabled facilities management. Journal of Construction Engineering and Management, 138(3), 431-442.

Botea, A., Müller, M., & Schaeffer, J. (2004). Near optimal hierarchical path-finding. Journal of Game Development, 1(1), 7-28.

Chen, Y. (2017). BIM-based research on indoor navigation techniques for emergency evacuation. Southwest Petroleum University.

Chen, X. B., & Kim, T. W. (2017). Automated mapping of user activities onto flexible space in space-use analysis. Journal of Construction Engineering and Management, 143(8), 04017034.

Cherry, E. (1999). Programming for design: From theory to practice. John Wiley & Sons.

Choi, B., Lee, H.-S., Park, M., Cho, Y. K. & Kim, H. (2014). Framework for work-space planning using four-dimensional BIM in construction projects. Journal of Construction Engineering Management, 140(9), 04014041.

Diakité, A. A., & Zlatanova, S. (2018). Spatial subdivision of complex indoor environments for 3D indoor navigation. International Journal of Geographical Information Science, 32(2), 213-235.

Ferguson, D. & Stentz, A. (2006). Using interpolation to improve path planning: The Field D* algorithm. Journal of Field Robotics, 23(2), 79-101.

Freitag, S., Weyers, B., & Kuhlen, T. W. (2017, March). Efficient approximate computation of scene visibility based on navigation meshes and applications for navigation and scene analysis. In 2017 IEEE Symposium on 3D User Interfaces (3DUI) (pp. 134-143). Los Angeles, California, USA.

Gibson, V. 2000. Evaluating office space needs and choices. University of Reading.

Hallberg, D., & Tarandi, V. (2011). On the use of open bim and 4d visualisation in a predictive life cycle management system for construction works. ITcon, 16, 445-466.

Hu, Z.-Z., Tian, P.-L., Li, S.-W., & Zhang, J.-P. (2018). BIM-based integrated delivery technologies for intelligent MEP management in the operation and maintenance phase. Advances in Engineering Software, 115, 1-16.

Ioannidis, D., Tzovaras, D., & Malavazos, C. (2012, July). Occupancy and business modelling. In The European Conference of Product and Process Modelling (ECPPM 2012). Reykjavik, Island.

Kim, T. W. (2013). Predicting space utilization of buildings through integrated and automated analysis of user activities and spaces. Stanford University.

Kim, T. W., Rajagopal, R., Fischer, M., & Kam, C. (2013). A knowledge-based framework for automated space-use analysis. Automation in Construction, 32, 165-176.

Kim, T. W., & Fischer, M. (2014a). Automated generation of user activity space pairs in space-use analysis. Journal of Construction Engineering and Management, 140(5), 04014007.

Kim, T. W., & Fischer, M. (2014b). Ontology for representing building users activities in space-use analysis. Journal of Construction Engineering and Management, 140(8), 04014035.

Liu, J., Ma, S., & Ma, S. (2011). Dynamic shortest path calculation based on improved Dijkstra algorithm. Journal of Systems Science and Information, 31(6), 1153-1157.

Manlises, C., Yumang, A., Marcelo, M., Adriano, A., & Reyes, J. (2016, November). Indoor navigation system based on computer vision using CAMShift and D* algorithm for visually impaired. In The 6th IEEE International Conference on Control System, Computing and Engineering (ICCSCE 2016) (pp. 481-484).Penang, Malaysia.

Nepal, M. P., Staub-French, S., & Pottinger, R. (2012). Querying a building information model for construction-specific spatial information. Advanced Engineering Informatics, 26(4), 904-923.

Pennanen, A. (2004). User activity based workspace definition as an instrument for workplace management in multi-user organizations. Helsinki: Haahtelakehitys Oy.

Pérez-Lombard, L., Ortiz, J., & Pout, C. (2008). A review on buildings energy consumption information. Energy and Buildings, 40(3), 394-398.

Rodenberg, O., Verbree, E., & Zlatanova, S. (2016). Indoor A* pathfinding through an octree representation of a point cloud. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4, 249-255.

Shen, W., Shen, Q., & Sun, Q. (2012). Building Information Modeling-based user activity simulation and evaluation method for improving designer–user communications. Automation in Construction, 21, 148-160.

Sun, X., Druzdzel, M. J., & Yuan, C. (2007, January). Dynamic weighting A* search-based MAP algorithm for Bayesian Networks. In Proceedings of the 20th International Joint Conference on Artificial Intelligence (pp. 2385-2390). Hyderabad, India.

Wang, D. (2012). Robot indoor path planning based on improved A* algorithm. Journal of Tsinghua University, 8, 1085-1089.

Wang, W., Dong, P., & Zhang, F. (2018). The shortest path planning for mobile robots using improved A* algorithm. Journal of Computer Applications, 38(5), 1523-1526.

Weiss, M. (1997). Data structures and algorithm analysis in C. Pearson.

Wu, H. M. & Gao, P. (2015). Application of BIM in residential space management of building projects. Project Management Techniques, 13(10), 57-63.

Xu, Y. (2007). Research on shortest path planning in vehicle navigation system. Jilin University.

Yan, L. (2018). Indoor positioning and navigation system design based on Wifi and sensors. Nanjing University of Posts and Telecommunications.

Zijlstra, E., Mobach, M. P., Van Der Schans, C., & Hagedoorn, M. (2014, June). Facilities planning promoting efficient space use at hospital building. In 13th EuroFM Research Symposium (pp. 366-377). Berlin, Germany.