IUCRC Planning Grant Embry-Riddle Aeronautical University: Center for Aviation Big Data Analytics [ABDA]

IUCRC 规划拨款 安柏里德航空大学：航空大数据分析中心 [ABDA]

• 批准号: 2231629
• 负责人: Hong Liu
• 金额: $ 2万
• 依托单位: Embry-Riddle Aeronautical University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2231629&HistoricalAwards=false
• 关键词: IUCRC; Planning; Grant; Embry; Riddle

The project seeks to address two fundamental issues: limited access to aviation big data; and shortage of a robust workforce with integrated big data analytics and aviation competencies. The proposed Center for Aviation Big Data Analytics (ABDA) will advance research and education through discovery and innovation at the confluence of big data analytics and aviation. Its mission is to develop big data analytics solutions specially designed for the aviation industry to ensure the safety, security, and prosperity of the U.S Aviation Ecosystem.ABDA has two sites: Embry-Riddle Aeronautical University (ERAU) and New Mexico State University (NMSU). The ABDA Center's research will focus on four thrust areas: (1) Data characterization and data requirement identification; (2) Development of next generation big data-enabled systems, services and applications; (3) Development of diverse ABDA-capable U.S. Workforce of the Future; and (4) Development of AI/machine learning solutions towards sustainable aviation. ERAU brings expertise in aviation data science and business analytics, flight research, unmanned aerial systems and autonomous systems, and aviation cybersecurity. Complementary expertise at other sites include energy-aware operations, flight energy consumption modeling, energy cost and emission assessment, artificial intelligence (AI), and machine learning. During the planning period, ERAU will explore ways to advance diversity and outreach with the Gaetz Aerospace Institute, the Boeing Scholars program, and the Women in Aviation Chapter through recruiting prospective students, educating current students, and identifying student researchers.The ABDA Center's research is expected to have three major societal implications: (1) to foster novel, transformative, multidisciplinary big data analytics/AI/machine learning approaches that ensure the safety, security, and prosperity of the U.S. Aviation Ecosystem, taking into consideration the unique challenges present in the aviation industry; (2) to foster a research community committed to advancing research and education at the confluence of big data analytics and aviation, and to transition its findings into industry practice; and (3) to collaborate with a minority serving institution site to recruit more underrepresented students and develop diverse ABDA-capable U.S. Workforce of the Future. All data, software, and artifacts produced in this project will be archived and preserved, according to standard institutional security and privacy practices and policies, for at least five years.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.

该项目旨在解决两个基本问题：获得航空大数据的机会有限;缺乏具有综合大数据分析和航空能力的强大劳动力。拟议中的航空大数据分析中心（ABDA）将通过大数据分析和航空融合的发现和创新来推进研究和教育。ABDA的使命是开发专为航空业设计的大数据分析解决方案，以确保美国航空生态系统的安全，保障和繁荣。ABDA有两个站点：安柏瑞德航空大学（ERAU）和新墨西哥州州立大学（NMSU）。ABDA中心的研究将集中在四个重点领域：（1）数据表征和数据需求识别;（2）开发下一代大数据支持的系统、服务和应用;（3）开发具有ABDA能力的多样化美国未来劳动力;（4）开发面向可持续航空的人工智能/机器学习解决方案。ERAU在航空数据科学和商业分析、飞行研究、无人机系统和自主系统以及航空网络安全方面拥有专业知识。其他站点的补充专业知识包括能源感知运营、飞行能耗建模、能源成本和排放评估、人工智能（AI）和机器学习。在规划期间，ERAU将与盖兹航空航天研究所（Gaetz Aerospace Institute）、波音学者项目（Boeing Scholars Program）和航空业女性分会（Women in Aviation Chapter）一起，通过招募未来学生、教育现有学生和确定学生研究人员，探索促进多样性和外联的方法。ABDA中心的研究预计将产生三大社会影响：（1）促进创新的、变革性的、多学科的大数据分析/人工智能/机器学习方法，以确保美国航空生态系统的安全、保障和繁荣，同时考虑到航空业面临的独特挑战;（2）培养一个致力于在大数据分析和航空融合方面推进研究和教育的研究社区，并将其研究成果转化为行业实践;（3）与少数服务机构合作，招募更多代表性不足的学生，并发展多样化的ABDA能力美国未来的劳动力。根据标准的机构安全和隐私实践和政策，该项目中产生的所有数据，软件和工件将被存档和保存至少五年。该奖项反映了NSF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。

项目成果

GraphDAC: A Graph-Analytic Approach to Dynamic Airspace Configuration

• DOI: 10.1109/iri58017.2023.00048
• 发表时间: 2023-07
• 期刊: 2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI)
• 作者: Ke-ke Feng;Dahai Liu;Yongxin Liu;Hong Liu;H. Song