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AI Institute: Planning: Construction

人工智能研究所：规划：建设

基本信息

批准号：
2020227
负责人：
Mani Golparvar-Fard
金额：
$ 50万
依托单位：
University of Illinois at Urbana-Champaign
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2020227&HistoricalAwards=false
关键词：
AI Institute Planning Construction

项目摘要

Improvements in the design, construction and operation of buildings and infrastructure projects will have a tremendous impact on the competitiveness of the U.S. Construction industry, by making projects more efficient, cheaper, faster, safer and more equitable. Nevertheless, enhancing project workflows poses problems that challenge current understanding of Artificial Intelligence (AI). This National Artificial Intelligence Research Institutes Planning award supports research and coordination activities to build collaborations among AI researchers, construction researchers, and industry partners, with the aim of forming an Institute for AI in Construction. Key goals are the identification of critical scientific problems, performance metrics, data sources, and future grand challenges. The team will also develop opportunities for educational activities that attract and retain skilled workforce in the industry. To do so, the team will offer a new course on Construction AI, formulate a new "CS+Construction" major, and design a Masters' capstone project sponsorship program, each with a strong element of entrepreneurship education. A mentoring program that aids students from underrepresented groups will be established particularly around their engagement in construction projects in the form of Women and Minority-Owned Business Enterprise (WMBE) firms. Many planning, monitoring, and control workflows involved in the design, construction, and operation of the built environment expose new challenges and opportunities for research in computer vision, natural language processing, and machine learning. Key technical problems, as identified by the National Academy of Engineering, include data-driven construction planning, monitoring work in progress, and real-time worker safety assessment. Solving these problems requires fundamental research in AI, such as: machine learning with many interconnected small-data problems; optimizing for application-specific objectives; leveraging both recognition and correspondence to recover geometry from images; and learning from loosely structured text documents. This research will identify AI problems in the construction domain that can serve as model problems, uncover novel conceptual challenges to AI research from construction applications, and identify likely dataset needs to support future research on AI in construction. Research findings will be disseminated through publications, presentations, and posting of datasets and software through a central project website.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

建筑和基础设施项目的设计、建造和运营方面的改进将对美国建筑业的竞争力产生巨大影响，使项目更高效、更便宜、更快、更安全、更公平。然而，增强项目工作流程带来了挑战当前对人工智能（AI）理解的问题。这项国家人工智能研究机构规划奖支持研究和协调活动，以建立人工智能研究人员、建筑研究人员和行业合作伙伴之间的合作，目的是组建一个人工智能建筑研究所。关键目标是确定关键的科学问题、性能指标、数据源和未来的重大挑战。该团队还将开发教育活动的机会，以吸引和留住行业中的熟练劳动力。为此，团队将开设一门新的建筑人工智能课程，制定一个新的“CS+建筑”专业，并设计一个硕士顶点项目赞助计划，每一个都具有很强的创业教育元素。将设立一个指导项目，帮助来自代表性不足群体的学生，特别是围绕他们以妇女和少数族裔拥有的企业（WMBE）公司的形式参与建筑项目。许多规划、监测和控制工作流程涉及到建筑环境的设计、建造和运营，这为计算机视觉、自然语言处理和机器学习的研究带来了新的挑战和机遇。国家工程院确定的关键技术问题包括数据驱动的施工规划、正在进行的工作监控和工人实时安全评估。解决这些问题需要人工智能的基础研究，例如：具有许多相互关联的小数据问题的机器学习；针对特定应用目标进行优化；利用识别和对应从图像中恢复几何形状；从结构松散的文本文档中学习。本研究将确定建筑领域的人工智能问题，这些问题可以作为模型问题，揭示建筑应用中人工智能研究的新概念挑战，并确定可能的数据集需求，以支持未来的建筑人工智能研究。研究成果将通过出版物、报告、数据集和软件通过一个中央项目网站进行传播。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。