Muhammad Bilal, Lukumon O. Oyedele, Junaid Qadir, K. Munir, Olúgbénga O. Akinadé, Saheed Ajayi, H. Alaka, H. Owolabi
{"title":"BIM软件关键特性分析与评价:构建基于大数据的建筑垃圾最小化插件","authors":"Muhammad Bilal, Lukumon O. Oyedele, Junaid Qadir, K. Munir, Olúgbénga O. Akinadé, Saheed Ajayi, H. Alaka, H. Owolabi","doi":"10.1080/2093761X.2015.1116415","DOIUrl":null,"url":null,"abstract":"The overall aim of this study is to investigate the potential of Building Information Modelling (BIM) for construction waste minimization. We evaluated the leading BIM design software products and concluded that none of them currently support construction waste minimization. This motivates the development of a plug-in for predicting and minimizing construction waste. After a rigorous literature review and conducting four focused group interviews (FGIs), 12 imperative BIM factors were identified that should be considered for predicting and designing out construction waste. These factors were categorized into four layers, namely the BIM core features layer, the BIM auxiliary features layer, the waste management criteria layer, and the application layer. Further, a process to carry out BIM-enabled building waste analysis (BWA) is proposed. We have also investigated the usage of big data technologies in the context of waste minimization. We highlight that big data technologies are inherently suitable for BIM due to their support of storing and processing large datasets. In particular, the use of graph-based representation, analysis, and visualization can be employed for advancing the state of the art in BIM technology for construction waste minimization.","PeriodicalId":38108,"journal":{"name":"International Journal of Sustainable Building Technology and Urban Development","volume":"6 1","pages":"211-228"},"PeriodicalIF":0.0000,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2093761X.2015.1116415","citationCount":"67","resultStr":"{\"title\":\"Analysis of critical features and evaluation of BIM software: Towards a plug-in for construction waste minimization using big data\",\"authors\":\"Muhammad Bilal, Lukumon O. Oyedele, Junaid Qadir, K. Munir, Olúgbénga O. Akinadé, Saheed Ajayi, H. Alaka, H. Owolabi\",\"doi\":\"10.1080/2093761X.2015.1116415\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The overall aim of this study is to investigate the potential of Building Information Modelling (BIM) for construction waste minimization. We evaluated the leading BIM design software products and concluded that none of them currently support construction waste minimization. This motivates the development of a plug-in for predicting and minimizing construction waste. After a rigorous literature review and conducting four focused group interviews (FGIs), 12 imperative BIM factors were identified that should be considered for predicting and designing out construction waste. These factors were categorized into four layers, namely the BIM core features layer, the BIM auxiliary features layer, the waste management criteria layer, and the application layer. Further, a process to carry out BIM-enabled building waste analysis (BWA) is proposed. We have also investigated the usage of big data technologies in the context of waste minimization. We highlight that big data technologies are inherently suitable for BIM due to their support of storing and processing large datasets. In particular, the use of graph-based representation, analysis, and visualization can be employed for advancing the state of the art in BIM technology for construction waste minimization.\",\"PeriodicalId\":38108,\"journal\":{\"name\":\"International Journal of Sustainable Building Technology and Urban Development\",\"volume\":\"6 1\",\"pages\":\"211-228\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/2093761X.2015.1116415\",\"citationCount\":\"67\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Sustainable Building Technology and Urban Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/2093761X.2015.1116415\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Sustainable Building Technology and Urban Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2093761X.2015.1116415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
Analysis of critical features and evaluation of BIM software: Towards a plug-in for construction waste minimization using big data
The overall aim of this study is to investigate the potential of Building Information Modelling (BIM) for construction waste minimization. We evaluated the leading BIM design software products and concluded that none of them currently support construction waste minimization. This motivates the development of a plug-in for predicting and minimizing construction waste. After a rigorous literature review and conducting four focused group interviews (FGIs), 12 imperative BIM factors were identified that should be considered for predicting and designing out construction waste. These factors were categorized into four layers, namely the BIM core features layer, the BIM auxiliary features layer, the waste management criteria layer, and the application layer. Further, a process to carry out BIM-enabled building waste analysis (BWA) is proposed. We have also investigated the usage of big data technologies in the context of waste minimization. We highlight that big data technologies are inherently suitable for BIM due to their support of storing and processing large datasets. In particular, the use of graph-based representation, analysis, and visualization can be employed for advancing the state of the art in BIM technology for construction waste minimization.
期刊介绍:
The International Journal of Sustainable Building Technology and Urban Development is the official publication of the Sustainable Building Research Center and serves as a resource to professionals and academics within the architecture and sustainability community. The International Journal of Sustainable Building Technology and Urban Development aims to support its academic community by disseminating studies on sustainable building technology, focusing on issues related to sustainable approaches in the construction industry to reduce waste and mass consumption, integration of advanced architectural technologies and environmentalism, sustainable building maintenance, life cycle cost (LCC), social issues, education and public policies relating to urban development and architecture .