Convergence Accelerator Phase I (RAISE): Preparing the Future Workforce of Architecture, Engineering, and Construction for Robotic Automation Processes
Convergence Accelerator Phase I (RAISE): Preparing the Future Workforce of Architecture, Engineering, and Construction for Robotic Automation Processes
批准号:
1937019
负责人:
Shahin Vassigh
金额:
$97.33万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2021-05-31
中文摘要
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英文摘要
The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future. The broader impact/potential benefits of this Convergence Accelerator Phase I project will address a crucial national problem by preparing the nation's workers and businesses in the Architecture, Engineering, and Construction (AEC) industries for an increasingly automated future workplace. This convergent research and development project involves researchers in architecture, construction, engineering, computer science, STEM education and economic development, as well as industry collaborators from the robotics, architecture, engineering, construction and software industries. Its Phase 1 deliverables will benefit businesses, workers and professionals in the AEC industry cluster, as well as regional and national economic development policy. Phase 1 provides the platform for critical solutions: maximizing employment opportunity, minimizing job displacement, and improving national economic competitiveness in the AEC industries. Improving AEC industry performance also promises solutions leading to a more energy efficient and sustainable built environment.This Convergence Accelerator Phase I project will contribute to research and application of Artificial Intelligence (AI) and immersive virtual environments in education as well as examining economic impacts of automation technology adoption in the AEC industries. The rapid adoption of AI and automation promises new employment and business opportunities, but will also create job displacement and business disruption. The Project's Phase 1 research objectives are to develop 1) a prototype interactive virtual reality robotics training and educational software package, and 2) a new model to measure the economic impact of automation adoption. Phase 1 will provide a platform for an immersive virtual software to teach new skills, improve process workflows, and increase efficiency in the AEC industries. Integrating advanced technologies including Reinforcement Learning, Computer Vision, Augmented and Virtual Reality, the project will advance methods of remote and on-site training for a large segment of employees in the AEC industries. By applying STEM learning strategies, the project will contribute to understanding how people learn in technology rich environments and bridge the gap between technology advancement and application to practice. The Project's economic analysis will utilize a "bottom-up" approach to estimating the employment impacts resulting from the adoption of AI and robotics.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.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Evolutionary Programming Based Deep Feature and Model Selection for Visual Data Classification
基于进化规划的视觉数据分类深度特征和模型选择
DOI:
10.1109/mipr49039.2020.00020
发表时间:
2020
期刊:
2020 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR
影响因子:
--
作者:
[Tian, Haiman, Chen, Shu-Ching, Shyu, Mei-Ling]
通讯作者:
Shyu, Mei-Ling
DOI:
10.1109/mipr49039.2020.00050
发表时间:
2020-08
期刊:
2020 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)
影响因子:
--
作者:
[Tianyi Wang;Yudong Tao;Shu‐Ching Chen;Mei-Ling Shyu]
通讯作者:
Tianyi Wang;Yudong Tao;Shu‐Ching Chen;Mei-Ling Shyu
Work in Progress: Towards an Immersive Robotics Training for the Future of Architecture, Engineering, and Construction Workforce
正在进行的工作:为建筑、工程和建筑劳动力的未来提供沉浸式机器人培训
DOI:
10.1109/edunine48860.2020.9149493
发表时间:
2020
期刊:
World Conference on Engineering Education
影响因子:
--
作者:
[Bogosian, Biayna, Bobadilla, Leonardo, Alonso, Miguel, Elias, Albert, Perez, Giancarlo, Alhaffar, Hadi, Vassigh, Shahin]
通讯作者:
Vassigh, Shahin
Augmented Learning for Environmental Robotics Technologies: A Data-Driven Approach for Sustainable Built Environments
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批准号:2315647
-
项目类别:Standard Grant
-
资助金额:$39.94万
-
财政年份:2023
-
负责人:Shahin Vassigh
-
依托单位:
Collaborative Research: Intelligent Immersive Environments for Learning Robotics
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批准号:2202610
-
项目类别:Standard Grant
-
资助金额:$74.97万
-
财政年份:2022
-
负责人:Shahin Vassigh
-
依托单位:
RAPID: A Platform for Mitigating the Impacts of COVID-19 on the Healthcare System
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批准号:2029557
-
项目类别:Standard Grant
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资助金额:$15.93万
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财政年份:2020
-
负责人:Shahin Vassigh
-
依托单位:
Collaborative Research: Strategies for Learning: Augmented Reality and Collaborative Problem-Solving for Building Sciences
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批准号:1504898
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项目类别:Standard Grant
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资助金额:$20.14万
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财政年份:2015
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负责人:Shahin Vassigh
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依托单位:
国内基金
海外基金
大规模非确定图数据分析及其Multi-Accelerator并行系统架构研究
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批准号:62002350
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项目类别:青年科学基金项目
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资助金额:24.0万元
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批准年份:2020
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负责人:张珩
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依托单位: