Multi-ontology fusion and rule development to facilitate automated code compliance checking using BIM and rule-based reasoning

Jiang, Liu; Shi, Jianyong; Wang, Chaoyu

doi:10.1016/j.aei.2021.101449

Cited by 44 publications

(12 citation statements)

References 32 publications

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“…To sum up, there are preliminary studies in information code review at home and abroad, but in the specification of the text structured method, the scope is relatively single and in the semantic enrichment of the building model, although some of the methods can correct the errors in the export of information 21 – 23 , but can not imply the applicability of such methods to solve such problems. As a result, it is still difficult to fully implement automated BIM review at this time.…”

Section: Literature Reviewmentioning

confidence: 99%

Automated code compliance checking research based on BIM and knowledge graph

Peng

Liu

2023

Sci Rep

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Automated code compliance checking plays an important role in moving the construction industry forward. While traditional drawing review relies on the identification of industry experts, the purpose of this study is to realize automatic code review by using BIM technology and knowledge graph technology. The method is based on knowledge graph to transform the specification provisions involved in the review of drawings into a computer-recognizable structured language using natural language processing technology to form a human–machine-readable knowledge graph pattern. For the review of BIM models, the BIM model information is exported and the global resource description framework of the building model is obtained in protégé, and the review report is finally obtained after mapping rules and review rules. Finally, the feasibility of the method is verified by an example. This study can effectively solve the problems of “manual dependency” and “inefficiency” in the process of review.

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Section: Literature Reviewmentioning

confidence: 99%

Automated code compliance checking research based on BIM and knowledge graph

Peng

Liu

2023

Sci Rep

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“…The three-level system consists of Top-level Ontology, Domain Ontology, and Application Ontology; the four-level system contains Top-level Ontology, Core Ontology, Domain Ontology, and Application Ontology. At the same time, there is a need for harmonisation in systems that meet different needs at different hierarchical levels by using several models and connecting several existing ontologies [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Ontological support system of managerial decision-making of production tasks for a food enterprise

Lutska¹,

Vlasenko²,

Ladanyuk³

et al. 2022

Tehnìka ta energetika

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Resource and energy efficiency of industrial production, in particular, food production, is a defining requirement that will ensure its functioning without loss of quality and quantity of final products. This is achieved by observing the requirements for the operational parameters of the company’s technological processes and their operational changes. Given the complexity of the functioning of the energy component of the world and Ukraine due to military operations and their consequences, the issue of quality/cost ratio has become more acute. Therefore, for large manufacturing enterprises, the development of systems for supporting management decision-making in accordance with the Industry 4.0 concept becomes relevant. This will contribute to improving the production and economic indicators of the enterprise through coordinated actions of all links of production activities by structuring and processing large amounts of heterogeneous information. The purpose of the study is to develop a decision support system for the task of choosing the structure of an automated control system based on an ontological knowledge base. The developed application ontology uses descriptive logic and is interpreted as part of a digital production double implemented by a single ontological knowledge base and ontological repository. Considering existing international standards, the OWL2 language was chosen for the implementation of the ontological knowledge base. The ontology system architecture contains an ontology server, a Node-Red application, and a user form. A project decision support system that issues recommendations based on requests for the structure of the control system for a technological facility with uncertainties, considering the requirements and restrictions set for each technological process of a food enterprise, reduces the time to choose the appropriate structures, schemes, and methods. Thus, the designer receives the necessary information, supported by knowledge from the subject area, for the synthesis of an effective automated control system. It is also assumed that the ontological system will be expanded by connecting new created applied ontologies that implement related tasks of an industrial enterprise

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“…Researchers have studied the topics of automated inspections of CCPs using BIM technology [2][3][4][5][6][7][8][9][10][11][12][13][14] as well as inspections involving GIS data [15].…”

Section: Introductionmentioning

confidence: 99%

Automated verification of information models for capital construction projects to mitigate environmental impact

Ostashev

2023

E3S Web Conf.

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Digitalisation of the construction industry is changing the processes of the sector and the use of information about the elements allows various automated checks to be carried out, including checks to reduce the environmental impact of capital construction projects. The study examines ways of dealing with such information, examples of verification algorithms and a means of determining the value of verification.

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Multi-ontology fusion and rule development to facilitate automated code compliance checking using BIM and rule-based reasoning

Cited by 44 publications

References 32 publications

Automated code compliance checking research based on BIM and knowledge graph

Automated code compliance checking research based on BIM and knowledge graph

Ontological support system of managerial decision-making of production tasks for a food enterprise

Automated verification of information models for capital construction projects to mitigate environmental impact

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