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推荐性出版物；(2)获得了一项专利；(3)6名博士和1名硕士学生毕业；(4)通过私人咨询、研讨会和供教育工作者和专业人员使用的计算机程序，向行业广泛转移技术。这项为未来五年提出的研究是申请者工作的继续，旨在为智能城市倡议引入新的进展，以满足很大一部分基础设施资产(加拿大79%)的需求，这些资产是旧的，需要昂贵的修复。这项研究将在四个主要领域寻求创新：(1)开发战略模拟模型，以研究政策(例如，预算水平和可持续性要求)对积压和长期基础设施性能的长期影响；(2)开发智能程序，使用图像分析和机器学习方法对建筑部件进行快速和自动的性能评估；(3)开发多年生命周期优化框架，以最大限度地从有限的修复资金中获得价值；以及(4)开发高级调度和项目控制模型，以支持考虑最后期限和预算限制的修复项目的有效交付。这项研究的直接成果是一个通用的智能基础设施修复框架，具有一个适合教育设施并可以适应其他基础设施资产的计算机化原型。战略和业务层面的整合在这项研究中是独一无二的，将支持哪些设施、何时以及如何更新设施的决策，以最大限度地提高康复支出的回报。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，从而最终减少积压，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更高的竞争优势。

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.