TY - GEN
T1 - Automating and optimizing spatial data processing workflows for civil infrastructure inspection
AU - Tang, Pingbo
AU - Pradhan, Anu
PY - 2012
Y1 - 2012
N2 - Limited resources are available to timely inspect and maintain the aging civil infrastructure across the United States. Reality capturing technologies, such as laser scanning, is replacing visual inspection and manual surveying for improved data qualities and reduced resource requirements, while bringing challenges of timely processing terabytes of spatial data. Even using state-of-art 3D reverse engineering environments, inspectors need to manually select data processing algorithms, compose and configure data processing workflows, and verify the correctness of these workflows. Such manual design and execution of spatial data processing workflows are tedious, and result in sub-optimal workflows that do not fully utilize time and resources for producing accurate and detailed spatial information needed by domain applications. This paper proposes a computational framework that will assist in the infrastructure inspection process through streamlined spatial data processing workflow generation, execution, and optimization. Based on previous studies on spatial information query, spatial data processing, and building information modeling (BIM), the authors are exploring the feasibility of automatically generating and optimizing spatial data processing workflows based on formalized representations of these workflows.
AB - Limited resources are available to timely inspect and maintain the aging civil infrastructure across the United States. Reality capturing technologies, such as laser scanning, is replacing visual inspection and manual surveying for improved data qualities and reduced resource requirements, while bringing challenges of timely processing terabytes of spatial data. Even using state-of-art 3D reverse engineering environments, inspectors need to manually select data processing algorithms, compose and configure data processing workflows, and verify the correctness of these workflows. Such manual design and execution of spatial data processing workflows are tedious, and result in sub-optimal workflows that do not fully utilize time and resources for producing accurate and detailed spatial information needed by domain applications. This paper proposes a computational framework that will assist in the infrastructure inspection process through streamlined spatial data processing workflow generation, execution, and optimization. Based on previous studies on spatial information query, spatial data processing, and building information modeling (BIM), the authors are exploring the feasibility of automatically generating and optimizing spatial data processing workflows based on formalized representations of these workflows.
KW - Automated planning
KW - Civil infrastructure inspection
KW - Laser scanning
KW - Scientific workflow
KW - Workflow generation
UR - http://www.scopus.com/inward/record.url?scp=84866251442&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84866251442&partnerID=8YFLogxK
U2 - 10.1061/9780784412329.091
DO - 10.1061/9780784412329.091
M3 - Conference contribution
AN - SCOPUS:84866251442
SN - 9780784412329
T3 - Construction Research Congress 2012: Construction Challenges in a Flat World, Proceedings of the 2012 Construction Research Congress
SP - 899
EP - 908
BT - Construction Research Congress 2012
T2 - Construction Research Congress 2012: Construction Challenges in a Flat World
Y2 - 21 May 2012 through 23 May 2012
ER -