@inproceedings{LiuSoibelmanWu2004, author = {Liu, Liang and Soibelman, Lucio and Wu, Jianfeng}, title = {Data Fusion and Modeling for Construction Management Knowledge Discovery}, doi = {10.25643/bauhaus-universitaet.125}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-1254}, year = {2004}, abstract = {Advances in construction data analysis techniques have provided useful tools to discover explicit knowledge on historical databases supporting project managers' decision making. However, in many situations, historical data are extracted and preprocessed for knowledge discovery based on time-consuming and problem-specific data preparation solutions, which often results in inefficiencies and inconsistencies. To overcome the problem, we are working on the development of a new data fusion methodology, which is designed to provide timely and consistent access to historical data for efficient and effective management knowledge discovery. The methodology is intended to be a new bridge between historical databases and data analysis techniques, which shields project managers from complex data preparation solutions, and enables them to use discovered knowledge for decision making more conveniently. This paper briefly describes the motivation, the background and the initial results of the ongoing research.}, subject = {Bauwerk}, language = {en} } @inproceedings{LiuSoibelmanTrupp2004, author = {Liu, Liang and Soibelman, Lucio and Trupp, Torsten}, title = {Novel Technologies for Construction Field Data Collection}, doi = {10.25643/bauhaus-universitaet.112}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-1120}, year = {2004}, abstract = {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.}, subject = {Mobile Computing}, language = {en} }