FW-HTF: Future of Firefighting and Career Training - Advancing Cognitive, Communication, and Decision Making Capabilities of Firefighters

FW-HTF：消防和职业培训的未来 - 提高消防员的认知、沟通和决策能力

• 批准号: 1840080
• 负责人: Aidong Lu
• 金额: $ 149.5万
• 依托单位: University of North Carolina at Charlotte
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1840080&HistoricalAwards=false
• 关键词: FW; HTF; Future; Firefighting; Career

The Future of Work at the Human-Technology Frontier (FW-HTF) is one of 10 new Big Ideas for Future Investment announced by NSF. The FW-HTF cross-directorate program aims to respond to the challenges and opportunities of the changing landscape of jobs and work by supporting convergent research. This award fulfills part of that aim. This project will enhance firefighting through a novel augmentation technology system. The project will involve advanced data, machines, tools, and human-technology relationships. Cognitive and social science studies will examine the impact of the new technology on human cognition and firefighters' work, training, and quality of life. The resulting augmentation technology will enhance the cognition, communication, and decision-making capabilities of firefighters. This project will have broader impacts at multiple levels ranging from individual firefighters to organizations and society. For firefighters, the new technology will enhance well-being and improve their job satisfaction and safety. The new technology will also help firefighters save lives and better protect property and the environment. The project's approach and result can be further extended to other types of emergency response workers, such as police, security, and disaster management and recovery.This convergent project will advance the research frontiers of technology and social science with a specialized, scalable, and adaptable data infrastructure. The project will involve new methods of multi-source non-intrusive data collection; model-based and learning-based analyses and fire modeling algorithms suited for data-rich environments; immersive and cross-platform visualizations improving on-site investigation; and multi-sensory interaction, communication, and decision-making mechanisms. Cognitive and social science research will reveal how the augmentation technology can transform the firefighter's work and provide guidance to effectively design human-technology interactions. The project will adopt a mixed-methods approach including lab experiments, two major public report data sources, and two-waves of surveys and interviews of firefighters. The research team will also develop multidisciplinary course modules for undergraduate and graduate students and tutorials to be offered at major conferences in order to recruit a broad participants including women and under-represented students. Both technical modules and education materials will be accessible through online platforms including GitHub after evaluation and improvements.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.

人类技术前沿的未来工作（FW-HTF）是NSF宣布的10个未来投资新想法之一。FW-HTF跨董事会计划旨在通过支持融合研究来应对不断变化的就业和工作环境的挑战和机遇。这个奖项实现了这个目标的一部分。该项目将通过一种新的增强技术系统加强消防。 该项目将涉及先进的数据、机器、工具和人与技术的关系。 认知和社会科学研究将研究新技术对人类认知和消防员工作，培训和生活质量的影响。 由此产生的增强技术将增强消防员的认知、沟通和决策能力。该项目将在多个层面产生更广泛的影响，从个人消防员到组织和社会。 对于消防员来说，新技术将提高他们的幸福感，提高他们的工作满意度和安全性。这项新技术还将帮助消防员拯救生命，更好地保护财产和环境。 该项目的方法和结果可以进一步扩展到其他类型的应急响应工作者，如警察，安全和灾难管理和恢复。这个融合的项目将推进技术和社会科学的研究前沿，具有专业化，可扩展性和适应性强的数据基础设施。 该项目将涉及多源非侵入式数据收集的新方法;基于模型和基于学习的分析以及适用于数据丰富环境的火灾建模算法;改善现场调查的沉浸式和跨平台可视化;以及多感官交互，通信和决策机制。 认知和社会科学研究将揭示增强技术如何改变消防员的工作，并为有效设计人机交互提供指导。 该项目将采用混合方法，包括实验室实验，两个主要的公共报告数据源，以及两波调查和消防员访谈。研究小组还将为本科生和研究生制定多学科课程模块，并在主要会议上提供辅导，以招募包括妇女和代表人数不足的学生在内的广泛参与者。 经过评估和改进后，技术模块和教育材料都将通过包括GitHub在内的在线平台访问。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

Skeletonmae: Spatial-Temporal Masked Autoencoders for Self-Supervised Skeleton Action Recognition

• DOI: 10.1109/icmew59549.2023.00045
• 发表时间: 2022-09
• 期刊: 2023 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)
• 作者: Wenhan Wu;Yilei Hua;Ce Zheng;Shi-Bao Wu;Chen Chen-Chen;Aidong Lu

ImWeb: cross-platform immersive web browsing for online 3D neuron database exploration

ImWeb：用于在线 3D 神经元数据库探索的跨平台沉浸式网页浏览

• DOI: 10.1145/3301275.3302319
• 发表时间: 2019
• 期刊: Proceedings of the 24th International Conference on Intelligent User Interfaces
• 作者: Fulmer, Willis;Mahmood, Tahir;Li, Zhongyu;Zhang, Shaoting;Huang, Jian;Lu, Aidong
• 通讯作者: Lu, Aidong

Alpaca: AR Graphics Extensions for Web Applications

Alpaca：Web 应用程序的 AR 图形扩展

• DOI: 10.1109/vr46266.2020.00036
• 发表时间: 2020
• 期刊: IEEE Conference on Virtual Reality and 3D User Interfaces (VR
• 作者: Hobson, Tanner;Duncan, Jeremiah;Raji, Mohammad;Lu, Aidong;Huang, Jian
• 通讯作者: Huang, Jian

Part Aware Contrastive Learning for Self-Supervised Action Recognition

• DOI: 10.48550/arxiv.2305.00666
• 发表时间: 2023-05
• 期刊: ArXiv
• 作者: Yilei Hua;Wen-Lan Wu;Ce Zheng;Aidong Lu;Mengyuan Liu;Chen Chen-Chen;Shiqian Wu

Toward cross-platform immersive visualization for indoor navigation and collaboration with augmented reality

• DOI: 10.1007/s12650-022-00852-9
• 发表时间: 2022-06
• 期刊: Journal of Visualization
• 影响因子: 1.7
• 作者: Akshay Ayyanchira;E. Mahfoud;Weichao Wang;Aidong Lu