Semi-automated site equipment selection and configuration through formal knowledge representation and inference |
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| Affiliation: | 1. LOGIQ Research Unit, University of Sfax, Tunisia;2. SMART Laboratory, High Institute of Management of Tunis, University of Tunis, Tunisia;3. International School of Business, Tunisia;1. Dept. of Civil and Architectural Engineering, Sultan Qaboos University, Muscat, Oman;2. Dept. of Civil and Environmental Engineering, Univ. of Alberta, Edmonton, AB T6G 2G2, Canada;1. Department of Interior Architecture Design, Hanyang University, Seoul 04763, Republic of Korea;2. Graduate School of Culture Technology, KAIST, Daejeon 305-701, Republic of Korea;1. Department of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, PR China;2. Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong;3. School of Civil Engineering and Built Environment, Queensland University of Technology (QUT), Australia;1. Department of Civil and Environmental Engineering, University of Waterloo, Canada;2. Department of Electrical and Computer Engineering, University of Waterloo, Canada |
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| Abstract: | The selection and configuration of site equipment is a fundamental part of construction preparation. Suitable site equipment supports the timely, cost-efficient and qualitative execution of the construction process. The use of planning tools based on formal knowledge management methods can both speed up the process of construction site planning and lead to better results. In this paper, we propose a rule-based knowledge inference system to support site equipment planners in a semi-automated manner using input data from building information models and working schedules. The knowledge-based system is built using the business rule management system Drools. Using a sample construction site, the feasibility of the proposed approach has been proven. |
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| Keywords: | Construction site equipment Building information modelling Knowledge based engineering |
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