Lacking of technologies for integrated and effective performance analyses, i.e., environmental, economic and safety analyses, for existing buildings during operation and maintenance period is now plaguing the city development in China. Based on the maintenance information model and actuated by information technologies such as Building Information Model/Modeling (BIM) and Artificial Intelligence (AI), this project combines the performance analysis methods, technologies and systems for existing buildings to construct a multi-scale maintenance BIM for different scaled objecs and different performance analysis requirements. Then a hybrid cloud architecture will be designed to achieve the integrated and efficient management of the big data within the multi-scale maintenance BIM. On this basis, a fusion mechanism for information between external-scale environment and internal-scale environment will also be studied. Through technology integration, system integration and application integration, a system named eBuilding will be designed and developed to achieve the multi-scale performance simulation and analysis for existing buildings. This research is expected to provide a complete set of theory, method, technology and software supports to timely discover the hidden performance damage and accordingly aid in solution developing. It also has the potential to promote sustainable development of cities, reduce resource consumption and safety risks.
Dr. Zhen-Zhong Hu is the Principal Investigator, and I’m the core memeber of the team.
Peng, Y., Lin, J.R., Zhang, J.P., Hu, Z.Z.* (2017). A Hybrid Data Mining Approach on BIM-based Building Operation and Maintenance. Building and Environment, 126, 483-495. doi: 10.1016/j.buildenv.2017.09.030
Xiao, Y., Hu, Z.*, Lin, J. (2019). Ontology-Based Semantic Retrieval Method of Energy Consumption Management. Advances in Informatics and Computing in Civil and Construction Engineering, 231-238. Springer International Publishing. Chicago,Illinois, US.
Leng, S., Hu, Z.Z.*, Luo, Z., Zhang, J.P., Lin, J.R. (2019). Automatic MEP Knowledge Acquisition Based on Documents and Natural Language Processing. Proceedings of the 36th CIB W78 2019 Conference, 800-809. Newcastle, United Kingdom.
A Hybrid Data Mining Method for Tunnel Engineering Based on Real-Time Monitoring Data from Tunnel Boring Machines
Leng, S., Lin, J.R., Hu, Z.Z.*, Shen, X. (2020). A Hybrid Data Mining Method for Tunnel Engineering Based on Real-Time Monitoring Data from Tunnel Boring Machines. IEEE Access, 8, 90430-90449. doi: 10.1109/ACCESS.2020.2994115
Yuan, S., Hu, Z.Z., Lin, J.R., Zhang Y.Y.* (2021). A Framework for the Automatic Integration and Diagnosis of Building Energy Consumption Data. Sensors, 21(4), 1395. doi: 10.3390/s21041395
Hu, Z.Z.*, Leng, S., Lin, J.R., Li, S.W., Xiao, Y.Q. (2021). Knowledge Extraction and Discovery Based on BIM: A Critical Review and Future Directions. Archives of Computational Methods in Engineering, 29(1), 335-356. doi: 10.1007/s11831-021-09576-9
Leng, S., Lin, J.R., Li, S.W., Hu, Z.Z.* (2021). A Data Integration and Simplification Framework for Improving Site Planning and Building Design. IEEE Access, 9, 148845-148861. doi: 10.1109/ACCESS.2021.3124010
Zhou, Y.C., Hu, Z.Z., Yan, K.X., Lin, J.R.* (2021). Deep Learning-based Instance Segmentation for Indoor Fire Load Recognition. IEEE Access, 9, 148771-148782. doi: 10.1109/ACCESS.2021.3124831
Zhang, Y.Y, Hu, Z.Z., Lin, J.R., Zhang, J.P.(2021). Data Cleaning for Prediction and its Evaluation of Building Energy Consumption. 2021 Proceedings of the 38th ISARC, 427-434. Dubai, UAE. doi: 10.22260/ISARC2021/0059
Zhang, Y.Y.*, Hu, Z.Z., Lin, J.R., Zhang, J.P. (2021). Data Management Framework for Building Energy Consumption. the 7th National Conference on Building Information Modeling, 536-540. China Architecture&Building Press. Chongqing, China.
Wu, L.T, Lin, J.R., Leng, S., Li, J.L., Hu, Z.Z. (2022). Rule-based Information Extraction for Mechanical-Electrical-Plumbing-Specific Semantic Web. Automation in Construction, 135, 104108. doi: 10.1016/j.autcon.2021.104108