Enhancement in Indian Bridge Management System using analytics within BIM data model

S. Joshi, Sitarama Raju Sagi
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引用次数: 1

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.
在BIM数据模型中使用分析增强印度桥梁管理系统
印度桥梁管理系统及其增强版统一桥梁管理系统(UBMS)与所有BMS一样,依靠连续的视觉观察来定义桥梁部件的状态评级,用于补救干预和关键管理决策。这些系统缺乏遇险的位置细节,并且在恶化和风险模型方面是被动的,因为它们依赖于干预评级的变化。结合摄影测量地理空间三维绘图/模型,将带来关键的缺失数据,提高IBMS/UBMS的有效性和效率。本文旨在提出一个在IBMS/UBMS中添加地理空间细节的概念。这种结合可以使用人工智能和机器学习来改进决策和报告。分析提供了一种预测工具来估计未来的压力和恶化过程的进展及其对未来性能的影响。也可能包括SHM数据。
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