dc.contributor |
Architecture |
|
dc.contributor |
Jones, James R. |
|
dc.contributor |
Ragon, Scott A. |
|
dc.contributor |
Ku, Ki-Hong |
|
dc.contributor |
Grant, Elizabeth J. |
|
dc.contributor |
Turkaslan Bulbul, Muhsine Tanyel |
|
dc.creator |
Charoenvisal, Kongkun |
|
dc.date |
2015-05-01T06:00:23Z |
|
dc.date |
2015-05-01T06:00:23Z |
|
dc.date |
2013-11-06 |
|
dc.date.accessioned |
2023-02-28T17:53:54Z |
|
dc.date.available |
2023-02-28T17:53:54Z |
|
dc.identifier |
vt_gsexam:1711 |
|
dc.identifier |
http://hdl.handle.net/10919/51953 |
|
dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/267029 |
|
dc.description |
There is a body of evidence indicating that the implementation of current Architecture, Engineering, and Construction (AEC) industry business models and practices have caused negative impacts on global energy supply, ecosystems, and local or regional economies. In order to eliminate such negative impacts, AEC practitioners are seeking new business models in which the Building Information Modeling (BIM) technology can be considered an important technology driver. Despite the fact that the majority of AEC practitioners have used BIM tools for construction-level modeling purposes, some early adopters of BIM technology began to use BIM tools to better inform their design decisions. Corresponding to the increasing demand for decision support functionality, a number of studies showed that a part of BIM technology will be developed toward decision support and artificial intelligence domains.
The use of computer-based systems to support decision making processes can usually be found in the business management field. In this field, decision support and business intelligence systems are widely used for improving the quality of managerial decisions. Because of its theories and principles, Decision Support Systems (DSS) can be considered as one of the potential information technologies that can be applied to enhance the quality of design decisions. The DSS also has the potential to be constructed as a system platform for implementing building information contained in BIM models associated with other databases, analytical models, and expert knowledge used by AEC practitioners.
This study explores an opportunity to extend the capability of BIM technology toward the decision support and artificial intelligence domains by applying the theories and principles of DSS. This research comprises the development of a prototype BIM interoperable web-based DSS for vegetated roofing system selection. The prototype development can be considered a part of an ongoing research agenda focusing on the development of the integrated web-based DSS for holistic building design conducted within the College of Architecture and Urban Studies (CAUS), Virginia Tech. Through a post-use interview study, the developed prototype is used as a tool for evaluating the possibility for the DSS development and the usefulness of DSS in improving the quality of vegetated roofing system design decisions. The understanding gained from the post-use study is used to create a guideline for developing a fully functional DSS for holistic building design that will be developed in the future. |
|
dc.description |
Ph. D. |
|
dc.format |
ETD |
|
dc.format |
application/pdf |
|
dc.format |
application/pdf |
|
dc.publisher |
Virginia Tech |
|
dc.rights |
In Copyright |
|
dc.rights |
http://rightsstatements.org/vocab/InC/1.0/ |
|
dc.subject |
Building Information Modeling (BIM) |
|
dc.subject |
Decision Support Systems (DSS) |
|
dc.subject |
Vegetated Roofing Systems |
|
dc.subject |
Industrial Foundation Classes (IFC) |
|
dc.subject |
Integrated Practice (IP) |
|
dc.subject |
Sustainable Architecture |
|
dc.title |
A BIM Interoperable Web-Based DSS for Vegetated Roofing System Selection |
|
dc.type |
Dissertation |
|