PFI:AIR - TT: SAFE (Situational Awareness for Events): A Data Visualization System

PFI:AIR - TT: SAFE（事件态势感知）：数据可视化系统

• 批准号: 1640736
• 负责人: Karen Smilowitz
• 金额: $ 19.94万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-15 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1640736&HistoricalAwards=false
• 关键词: PFI; AIR; TT; SAFE; Situational

This PFI: AIR Technology Translation project focuses on translating operations research models and data analytics to improve situational awareness and decision making for mass gathering events. Such mass gathering events are growing in popularity, and thus require significant resources to ensure safety and success. To date, event management tools have not grown to meet this need. This project is designed to address these gaps in event management tools. The research proposed in this project significantly expands the development of a Data Visualization System focused on medical preparedness for mass gathering events, originally conceived for marathons. This system was created for event organizers and relevant stakeholders to effectively manage and oversee all participants, monitor the dynamic location of participants, and manage health and safety resources throughout the event, both under normal operating conditions and in the event that emergency issues arise. The system provides a dynamic representation of the flow of people and resources: at the core is a novel simulation tool that predicts and displays runner density on the course over time. The data visualization system is the first comprehensive dashboard for endurance event management. The project will result in a significant ramp-up of the current prototype of the data visualization system to expand functionality and make the system more turn-key. The project will also result in the development of a business plan for commercialization, working with Northwestern University's Innovations and New Ventures Office (INVO). While this system was initially developed for marathons, its applicability can go beyond endurance events.This project addresses several important technology gaps as it translates from research discovery toward commercial application. The innovation of the data visualization system comes from the integration of data visualization, participant and resource flow simulation, event data, and event management services. As such, the next steps towards commercialization will require advances in data analytics related to event data and operations research decision tools that leverage the data analysis. System capabilities will be expanded in new directions to allow us to scale up the technology for broader applicability. The project focuses in three areas: (1) upgrading the simulation model to capture additional flows of resources and participants; (2) merging new streams of event data to more fully capture the nuances of mass gathering events, and (3) developing new event management services that improve decision making for mass gathering events. In addition, personnel involved in this project, undergraduate and graduate students, will receive innovation and entrepreneurship experiences through INVO. In particular, INVO offers a series of internship and fellowship programs for these students.The project engages experts in event management and emergency response to guide commercialization aspects, specifically focusing on needed system functionalities in this technology translation effort from research discovery toward commercial reality.

该PFI：AIR技术翻译项目专注于翻译运筹学模型和数据分析，以提高对大规模集会活动的态势感知和决策能力。 这种大规模集会活动越来越受欢迎，因此需要大量资源来确保安全和成功。到目前为止，事件管理工具还没有发展到满足这一需求。 该项目旨在解决事件管理工具中的这些差距。 该项目中提出的研究大大扩展了数据可视化系统的开发，该系统专注于为大规模聚集事件做好医疗准备，最初是为马拉松而设计的。该系统是为活动组织者和相关利益相关者创建的，以有效地管理和监督所有参与者，监控参与者的动态位置，并在整个活动期间管理健康和安全资源，无论是在正常操作条件下还是在出现紧急问题时。 该系统提供了人员和资源流动的动态表示：核心是一种新颖的模拟工具，可以预测和显示随着时间的推移球场上的跑步者密度。 数据可视化系统是首个用于耐力赛事管理的综合仪表板。 该项目将导致数据可视化系统目前原型的大幅提升，以扩大功能，使系统更具交钥匙功能。 该项目还将与西北大学的创新和新风险投资办公室（INVO）合作，制定商业化的商业计划。虽然该系统最初是为马拉松而开发的，但其适用性可以超越耐力赛。该项目解决了从研究发现到商业应用的几个重要技术差距。 数据可视化系统的创新之处在于将数据可视化、参与者和资源流模拟、事件数据和事件管理服务集成在一起。因此，商业化的下一步将需要与事件数据相关的数据分析和利用数据分析的运筹学决策工具的进步。 系统功能将在新的方向上扩展，使我们能够扩大技术的适用性。 该项目侧重于三个领域：（1）升级模拟模型，以捕捉更多的资源和参与者流;（2）合并新的事件数据流，以更全面地捕捉大规模聚集事件的细微差别;以及（3）开发新的事件管理服务，以改善大规模聚集事件的决策。 此外，参与该项目的人员，本科生和研究生，将通过INVO获得创新和创业经验。 INVO特别为这些学生提供了一系列的实习和奖学金计划。该项目聘请了事件管理和应急响应方面的专家来指导商业化方面的工作，特别关注从研究发现到商业现实的技术转化工作中所需的系统功能。

项目成果

SAFE: A Comprehensive Data Visualization System

• DOI: 10.1287/inte.2019.0989
• 发表时间: 2019-07-01
• 期刊: INFORMS JOURNAL ON APPLIED ANALYTICS
• 影响因子: 1.4
• 作者: Basdere, Mehmet;Caniglia, Gabriel;Smilowitz, Karen
• 通讯作者: Smilowitz, Karen