Smart City Rehabilitation

在过去的六年里，申请人在建筑和资产管理方面的研究活动对该领域做出了重大贡献，表现在：（1）与学生和同事一起发表了大量参考出版物;（2）一项专利;（3）6名博士毕业。硕士研究生1名;以及（4）通过私人咨询、讲习班和供教育工作者和专业人员使用的计算机程序，向工业界广泛转让技术。未来五年的研究是申请人工作的延续，旨在为智慧城市计划引入新的进步，以满足大部分基础设施资产（加拿大79%）的需求，这些资产陈旧且需要昂贵的修复。本研究将在四个主要方面寻求创新：（1）开发战略模拟模型，以研究政策的长期影响（例如，（2）制定智能程序，利用图像分析和机器学习方法对建筑物构件进行快速和自动的性能评估;（3）制定多年生命周期优化框架，以最大限度地利用有限的修复资金实现价值;以及（4）开发先进的调度和项目控制模型，以支持考虑期限和预算限制的康复计划的有效交付。该研究的直接成果是一个通用的智能基础设施修复框架，该框架具有适合教育设施的计算机化原型，并可以适应其他基础设施资产。战略和运营层面的整合是独一无二的，在这项研究中，将支持哪些，何时，以及如何更新设施，以最大限度地提高康复支出的回报的决定。拟议的基础研究支持制定更好的基础设施管理政策和实施工具，从而最终导致积压减少，提高可持续性，更智能的加拿大城市，以及加拿大基础设施管理公司的更高竞争优势。

SMART CITY REHABILITATION In the past six years, the applicant's research activities in construction and asset management have resulted in significant contributions to the field as shown by: (1) a large number of refereed publications with students and co-workers; (2) one patent; (3) graduation of 6 Ph.D. and 1 Master's students; and (4) extensive technology transfer to industry through private consultation, workshops, and computer programs for use by educators and professionals. The research proposed for the next five years is a continuation of the applicant's work and aims to introduce new advancements to smart city initiatives to address the needs of a large portion of infrastructure assets (79% in Canada) that are old and require costly rehabilitation. The research will seek innovations in four main areas: (1) Developing a strategic simulation model to examine the long-term influences of policies (e.g., budget levels and sustainability requirements) on backlog accumulation and long-term infrastructure performance; (2) Developing intelligent procedures for fast and automated performance assessment of building components using image analysis and machine learning methods; (3) Developing a framework for multi-year life cycle optimization to maximize the value gained from the limited rehabilitation dollars; and (4) Developing an advanced scheduling and project control model to support effective delivery of rehabilitation programs considering deadlines and budget constraints. The direct outcome of the research is a generic smart infrastructure rehabilitation framework with a computerized prototype that suits educational facilities and can be adapted to other infrastructure assets. The integration of strategic and operational dimensions is unique in this research and will support decisions of which, when, and how to renew facilities to maximize the return on rehabilitation spending. The proposed fundamental research supports developing better infrastructure management policies and implementation tools, thus ultimately leading to backlog reduction, improved sustainability, smarter Canadian cities, and higher competitive advantage of Canadian infrastructure management companies.