AI Institute: Planning: Construction

建筑和基础设施项目的设计、建造和运营的改进将使项目更高效、更便宜、更快、更安全和更公平，从而对美国建筑业的竞争力产生巨大影响。然而，加强项目工作流程会带来挑战当前对人工智能(AI)的理解的问题。这个国家人工智能研究院和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，目的是建立一个建筑人工智能研究所。关键目标是确定关键的科学问题、绩效指标、数据源和未来的重大挑战。此外，该团队还将为教育活动开发机会，以吸引和留住行业中的熟练劳动力。为此，该团队将开设一门关于建筑AI的新课程，制定一个新的“CS+建筑”专业，并设计一个大师顶峰项目赞助计划，每个项目都有很强的创业教育元素。将特别围绕妇女和少数族裔企业(WMBE)公司的形式参与建筑项目，建立一个指导计划，帮助来自代表性不足群体的学生。许多涉及建筑环境设计、施工和运营的规划、监控和控制工作流程给计算机视觉、自然语言处理和机器学习的研究带来了新的挑战和机遇。美国国家工程院确定的关键技术问题包括数据驱动的建筑规划、监控正在进行的工作和实时工人安全评估。要解决这些问题，需要在人工智能方面进行基础研究。例如：具有许多相互关联的小数据问题的机器学习；针对应用特定的目标进行优化；利用识别和对应从图像中恢复几何图形；以及从松散结构的文本文档中学习。这项研究将确定建筑领域中可用作模型问题的人工智能问题，揭示建筑应用对人工智能研究的新的概念挑战，并确定可能的数据集需求，以支持未来对建筑中的人工智能的研究。研究成果将通过出版物、演示文稿和通过中央项目网站发布的数据集和软件来传播。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.