The paper presents the ongoing experimentation of a Computer Supported Design Studio (CSDS). CSDS is part of our continuing effort to integrate computers and networks in the design studio. We recognise three corner stones to CSDS: memory, process and collaboration. They offer a framework for the interpretation of the pedagogical aspects of the teaching of architectural design in relation to the innovations produced by information and communication technologies. The theme of the 1998 CSDS is a railway station in Turin, Italy, to be incorporated in a reorganised rail transport system. The choice of this theme emphasises the realistic simulation aspects of the studio, where technical problems need to be interpreted from an architectural point of view
The current necessity of manage complexity in the field of building process management push to provide process' figures of construction methodologies and tools capable to support them in a proficient way. With the scope to define in advance the places occupied by workers to accomplish a task, is defined a methodology and related tools to integrate Building Information Modeling (BIM) with an Agent-Based simulation of workers activities. The goal is to know at early project phases where it is possible to work in a more effective and safer way, how it is possible to be more efficient placing in the same working space different working phases and when it is possible to allow the continuity of building operations. The outcome of the system is predicting how much resources are involved in a project, identifying and minimizing wasted time.
Purpose This paper reports on the development of intelligent probabilistic models for real-time estimation of construction progress, which operate on the basis of a continuous data flow collected by monitoring networks deployed on-site. Several authors listed the advantages that would be provided by the availability of such models, like project performance and quality control, timely onsite inspections, better control of health and safety prescriptions against job injuries and fatalities. The findings reported in this paper represent a feasibility study and preliminary examples of Bayesian Networks, which are able to infer the work progress attained at every step, starting from real-time tracks of the construction site activities. Activity tracks are represented as a set of state variables figuring out workers' effort, equipment and materials usage rates and other knowledge about the context. Method As estimations are always related to dynamic processes, Dynamic Object Oriented Bayesian Networks have been used to develop a set of first order Hidden Markov Models. Hence, the models are arranged as a sequence of time steps, where each time step propagates evidences collected by the site monitoring sensor network along the time line. The actual cumulative progress is computed as a function of the progress achieved in each time step. Models representing a number of typical tasks (external piping, onsite cast of reinforced concrete floor slab, walls erection, ceiling installation) for a real case of a construction site have been developed. Their structure has been designed as part of a general monitoring framework, covering all the phases from design to execution, where BIM design, monitoring systems, methodological process innovations, intelligent inferences and advanced visualization are combined. Results & Discussion The networks have been developed and validated through data collected from a real case, and they have been shown to be able to infer work progress, the accuracy of which depends on the resolution and quality of the collected data.
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