Enhancement in Indian Bridge Management System using analytics within BIM data model
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Bibliographic Details
| Author(s): |
Sachidanand Joshi
(IDDC Engineers Pvt. Ltd., Mumbai, India)
Sitarama Raju Sagi (IDDC Engineers Pvt. Ltd., Mumbai, India) |
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| Medium: | conference paper | ||||
| Language(s): | English | ||||
| Conference: | IABSE Symposium: Challenges for Existing and Oncoming Structures, Prague, Czech Republic, 25-27 May 2022 | ||||
| Published in: | IABSE Symposium Prague 2022 | ||||
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| Page(s): | 903-910 | ||||
| Total no. of pages: | 8 | ||||
| DOI: | 10.2749/prague.2022.0903 | ||||
| Abstract: |
Indian Bridge Management System and its enhanced version Unified Bridge Management System (UBMS) like all BMS rely on successive visual observations to define status ratings of bridge components which are used for remedial interventions and critical management decisions. These systems are devoid of location details of distress and are reactive in regard to deterioration and risk models as they rely on such changes in ratings for interventions. Incorporating photogrammetric geospatial 3D drawing/model will bring critical hereto missing data to enhance effectiveness and efficiency of IBMS/UBMS. This paper is aimed to present a concept for adding geospatial details to IBMS/UBMS. This incorporation enables the usage of AI and machine learning for improved decision making and reporting. Analysis provides a predictive tool to estimate future distress and the progression of deterioration process and the impact it can have on the future performance. Inclusion of SHM data will also be possible. |
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| Keywords: |
photogrammetry artificial intelligence deterioration model Unified Bridge Management System Predictive analysis
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| Copyright: | © 2022 International Association for Bridge and Structural Engineering (IABSE) | ||||
| License: | This creative work is copyrighted material and may not be used without explicit approval by the author and/or copyright owner. |
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