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Site superintendents performing project management tasks on construction sites need to access project documents and need to collect information that they observe while inspecting the site. Often, information that is observed on a construction site needs to be integrated into electronic documents or project control systems. In the future, we expect integrated product and process models to be the medium for storing and handling construction project management information. Even though mobile computing devices today are already capable of storing and handling such integrated product and process data models, the user interaction with such large and complex models is difficult and not adequately addressed in the existing research. In this paper, we introduce a system that supports project management tasks on construction sites effectively and efficiently by making integrated product and process models accessible. In order to effectively and efficiently enter or access information, site superintendents need visual representations of the project data that are flexible with respect to the level of detail, the decomposition structure, and the type of visual representation. Based on this understanding of the information and data collection needs, we developed the navigational model framework and the application Site Data Collection System (SiDaCoS), which implements that framework. The navigational model framework allows site superintendents to create customized representations of information contained in a product and process model that correspond to their data access and data collection needs on site.
This paper describes monitoring of the in-valley discharge and underground water level at the place where the tunnel will be constructed and also, the numerical analysis for prediction applying the Tank Model and Linear Filter Method to calculate the prediction. The application of these analyses has actually allowed the change of underground water level to be grasped and more effective information system to be established by comparing the real-time monitoring data with the real-time calculation of prediction.
A distributed geotechnical remote analysis of data system (Distributed G-RAD) can benefit both owners and contractors in providing better quality control and assurance on geotechnical projects. The Distributed G-RAD approach involves efficient data acquisition using PDAs with GPS capability, radio frequency identification (RFID) tags for labeling soil samples, laser scanning for measuring lift thickness and volumes of stockpiles and borrow pits. Spatial data storage is provided using a geographic information system (GIS). Portions of this system are already developed while other parts are still being considered. This paper also describes how RFID and laser scanning technologies can be used in the larger Distributed G-RAD system.
A vast growth of advanced information technology systems and tools nowadays is opening new ways to collect accurate as-built data. Since the turn of the millennium, new technology developments enable for the first time to gather accurate as-built information. Accurate as-built data will be of great usage to construction management as well as to designers and engineers. Given that most of the planned data are already digitally available, as-built data remains on paper forms. Information technology developments are opening new ways to digitize construction field data in order to develop intelligent tools for construction management allowing design engineers to update as-planned data. 3D Laser scanning, digital close-range photogrammetry and mobile computing are among the promising data collection technologies, which are auspicious to create new opportunities to develop advanced construction management and engineering tools. Primarily, accurate collected as-built data will be highly beneficial for the process of updating as-planned data.
This paper presents a generic methodology for measurement system configuration when the goal is to identify behaviour models that reasonably explain observations. For such tasks, the best measurement system provides maximum separation between candidate models. In this work, the degree of separation between models is measured using Shannon’s Entropy Function. The location and type of measurement devices are chosen such that the entropy of candidate models is greatest. This methodology is tested on a laboratory structure and, to demonstrate generality, an existing fresh water supply network in a city in Switzerland. In both cases, the methodology suggests an appropriate set of sensors for identifying the state of the system.
The design of mobile IT systems, especially the design of wearable computer systems, is a complex task that requires computer science knowledge, such as that related to hardware configuration and software development, in addition to knowledge of the domain in which the system is intended to be used. Particularly in the AEC sector, it is necessary that the support from mobile information technology fit the work situation at hand. Ideally, the domain expert alone can adjust the wearable computer system to achieve this fit without having to consult IT experts. In this paper, we describe a model that helps in transferring existing design knowledge from non-AEC domains to new projects in the construction area. The base for this is a model and a methodology that describes the usage scenarios of said computer systems in an application-neutral and domain-independent way. Thus, the actual design information and experience will be transferable between different applications and domains.