Keeping Infrastructure Safe During the COVID-19 Pandemic using Artificial Intelligence

保持我们的基础设施（桥梁、道路、建筑物）处于安全和可操作的状态是一项重大挑战。新型冠状病毒疫情导致工程及建筑行业突然停顿，可能会使意外及灾难的风险高于正常水平。当安全受到损害时，整个基础设施系统变得无效，公共安全受到巨大威胁。为了避免这种情况，对高效的基础设施管理系统的需求怎么强调都不过分。拟议的研究旨在展示数据分析和机器学习模型如何帮助基础设施所有者和管理人员利用现有的检查和竣工数据，在疫情封锁阶段预测现有结构的状况。这将有助于识别所有工程现场封锁期间存在的安全隐患，无论是建筑物、桥梁还是其他基础设施。利用机器学习算法中的COVID-19传播和中断数据，本研究将调查封锁沿着修订的正在进行的工作方法或改变的监督做法如何影响加拿大基础设施的结构安全。本研究旨在开发一种决策支持工具，以便根据可能的级联效应识别风险知情的关键基础设施，以解决未来封锁期间基础设施老化和恶化的问题。结合申请人沿着的专业知识和来自TBT工程有限公司的经验丰富的行业人员，该项目将开发一种先进的工具，以加强关键基础设施的决策，提高安全性，减少意外关闭和/或故障。这项研究还将有助于TBTE提供专业服务，这将在加拿大基础设施行业在大流行期间管理此类紧急情况方面发挥重要作用。拟议研究的成功完成将为加拿大基础设施网络抵御封锁带来的不确定性铺平道路。

Keeping our infrastructure (bridges, roads, buildings) in safe and operational condition is a major challenge. The sudden pause in engineering and construction sector due to the COVID-19 pandemic can elevate the risk of unwanted accidents and mishaps above normal. When the safety is compromised, the overall infrastructure system becomes ineffective and public safety is under immense threat. To avoid such scenarios, the need for an efficient infrastructure management system cannot be overstated. The proposed research is designed to demonstrate how data analytics and machine learning models can help infrastructure owners and managers predict the condition of existing structures during the lockdown phase of this pandemic, using already available inspection and as-built data. This will aid in identifying safety hazards present during lockdowns at all engineered sites, whether for buildings, bridges or other infrastructure. Using COVID-19 spread and disruption data in a machine learning algorithm, this study will investigate how lockdowns along with revised ongoing-work methods or changed supervision practices could affect structural safety of Canadian infrastructure. This research aims to develop a decision support tool to enable risk-informed critical infrastructure identification based on possible cascade effects for addressing issues pertaining to aging and deteriorating infrastructure during future lockdowns. Combining the expertise of the applicant along with the experienced industry personnel from TBT Engineering Ltd., this project will develop an advanced tool with respect to enhance decision making on critical infrastructure to increase safety and decrease unexpected shutdown and/or failure. This research will also help TBTE to provide specialized services, which will play a significant role in the Canadian infrastructure industry to manage such emergencies during pandemic. The successful completion of the proposed research will pave the way toward resiliency of Canada's infrastructure network against the uncertainty arising from the lockdown.