Zhenzhong Hu

    He recieved both his BE and PhD degree in the Department of Civil Engineering at Tsinghua University, China. He was a visiting researcher in Carnegie Mellon University.
    He is now the associate professor in Shenzhen International Graduate School, Tsinghua University, and also the secretary general of the BIM Specialty Committee of the China Graphics Society.
    His research interests include information technologies in civil and marine engineering, building information modeling (BIM) and digital disaster prevention and mitigation.
  • 2021-03-01

    "Linking data model and formula to automate KPI calculation for building performance benchmarking" has been published in Energy Reports.

    Buildings consume a large proportion of global primary energy and building performance management requires massive data inputs. Key Performance Indicator (KPI) is a tool used for comparing different buildings while avoiding problems caused by heterogeneous data sources. However, silos of building and energy consumption data are separate, and the linkages between a KPI formula and different data sets are often non-existent. This paper develops an ontology-based approach for automatically calculating the KPI to support building energy evaluation. The proposed approach integrates building information from BIM and energy and environmental information collected by sensor networks. A KPI ontology is developed to establish a KPI formula, thereby linking static and dynamic data generated in the building operation phase. Each KPI can be defined by inputs, a formula and outputs, and the formula consists of parameters and operators. The parameters can be linked to building data or transformed into a SPARQL query. A case study is investigated based on the proposed approach, and the KPIs for energy and environment are calculated for a real building project. The result shows that this approach relates the KPI formula to the data generated in the building operation phase and can automatically give the result after defining the space and time of interest, thus supporting building performance benchmarking with massive data sets at different levels of details. This research proposes a novel approach to integrating the KPI formula and linked building data from a semantic perspective, and other researchers can use this approach as a foundation for linking data from different sources and computational methods such as formula created for building performance evaluation.

    Note: Energy Reports is an important academic journal in the field of energy research. Its impact factor in 2019 is 3.595, and it is listed in the Q2 SCI journals.

  • 2021-2-17

    A Framework for the Automatic Integration and Diagnosis of Building Energy Consumption Data has been published in Sensors .

    Buildings account for a majority of the primary energy consumption of the human society, therefore, analyses of building energy consumption monitoring data are of significance to the discovery of anomalous energy usage patterns, saving of building utility expenditures, and contribution to the greater environmental protection effort. This paper presents a unified framework for the automatic extraction and integration of building energy consumption data from heterogeneous building management systems, along with building static data from building information models to serve analysis applications. This paper also proposes a diagnosis framework based on density-based clustering and artificial neural network regression using the integrated data to identify anomalous energy usages. The framework and the methods have been implemented and validated from data collected from a multitude of large-scale public buildings across China. This research proposes a general framework for building energy consumption big data management and analysis, provides a basis for building energy consumption data application, and has certain reference significance on diagnosis and decision making of saving building energy consumption.

    ps. Information for Sensors: Impact Factor: 3.275 (2019);Ranked 17/129 (Q1) in 'Physics and Astronomy: Instrumentation' and 147/670 (Q1) in 'Electrical and Electronic Engineering' and 70/300 (Q1) in 'Computer Science: Information Systems'

  • 2021-01-20

    I was invited to to organize a special issue on "Smart Sensing in Building and Construction(SSBC)" in Sensors (Impact Factor: 3.275) together with Jia-Rui Lin from Tsinghua University, Jérômex Frisch from RWTH Aachen University, Qian Wang from National University of Singapore, Yichuan Deng from South China University of Technology and Yi Tan from Shenzhen University. The deadline for submission is 31st October this year. Welcome to submit your manuscript for potential publication.

  • 2021-01-06

    Beijing Cloud Jianxin Technology Co., Ltd. signed a strategic cooperation agreement with Haina Cloud Technology Holding Co., Ltd. of Haier Group. Based on their respective industry accumulation and advantageous resources, Cloud Jianxin and Haina Cloud will carry out in-depth strategic cooperation in BIM intelligent product development and other fields, build industry benchmark and model project through product development and project cooperation, and play a leading role in development and innovation. The two sides will work together to create intelligent BIM products and explore the road of Building Internet.

    Note: Beijing Cloud Jianxin Technology Co., Ltd., which is responsible for the transformation of research results of this research group, is committed to BIM and intelligent information technology products and services, and is a leading provider of BIM platform, software and service for the whole life cycle of building in China.

  • 2020-12-31

    "Application Standard of Building Information Model Technology in Guizhou Province", a local standard for engineering construction in the People's Republic of China, was officially issued by the Department of Housing and Urban-Rural Development of Guizhou Province. This standard is numbered DBJ52/T101-2020 and will be implemented from March 1, 2021. I participated in the compilation as the second main author. This standard is prepared on the basis of: 1) the requirements of "Notice on the issuance of the 2013 Plan for the Formulation and Revision of Engineering Construction Standards and Specifications" (Jian Biao [2013] No.6); 2) the extensive investigation and research as well as the earnest summary of practical experience by the standard preparation group; 3) the reference of relevant international and national standards; 4) the extensive solicitation of opinions. This standard consists of 12 chapters and 6 appendixes and explanations, and the main contents include: general provisions, terms, basic regulations, application environment, application organization and management, model creation and management, BIM application in feasibility study and planning stage, BIM application in survey and design stage, BIM application in construction stage, BIM application in operation and maintenance stage, BIM application in engineering cost, BIM based big data application, and appendixes and explanations, etc.