Spatiotemporal Analysis of 9-1-1 Call Stream Data

9-1-1通话流数据的时空分析

• 批准号: 0429448
• 负责人: Chaitanya Baru
• 金额: $ 60万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0429448&HistoricalAwards=false
• 关键词: Spatiotemporal; Analysis; Call; Stream; Data

This award will support a partnership among the University of California San Diego, the State of California Governor's Office of Emergency Services (OES), and the Public Safety Network (PSN) company. The goal is to perform spatiotemporal analysis of 9-1-1 call stream data and correlate these data to external events, in order to provide more effective and efficient response during emergencies. A wide variety of existing and emerging data sources are of potential value in helping the OES determine the location and magnitude of incipient disasters, and timely access to these data is critical for OES to manage State-level resources and to assist local governments in providing aid to disaster victims. PSN has been contracted by California to collect 9-1-1 call stream data across the State. PSN collects data from several hundred distinct Public Safety Answering Points (PSAP's) for about 60-80,000 emergency calls per day. Researchers from UC San Diego's San Diego Supercomputer Center and Scripps Institution of Oceanography will work with PSN and OES to provide expertise in advanced data management, data analysis, data mining, and statistical techniques, with the objective of performing spatiotemporal analysis of 9-1-1 emergency call stream data across the State of California and correlating these data with external information, such as earthquakes and fires.PSN will provide an archival dataset of 9-1-1 call stream data for the 4-year period preceding the start of the project. The analysis will include correlation of this information with external event information, such as earthquakes and wildfires, to determine spatiotemporal signature of such events. This information will then be used to establish alarm thresholds to provide advance warning to first responders and other emergency service personnel, concerning the spatial extent and temporal evolution of an emergency event. The long-termgoal is also to enable the use of this information for real-time detection of emergency events in order to provide rapid response at the local level and facilitate decision support for resource allocation and planning at the State level.Intellectual Merit - Analysis of 9-1-1 call stream data will provide a better understanding of the spatiotemporal patterns of emergency calls and their correlation to external events. Predictive models built with this data can lead to real-time decision support and better overall planning to enable more efficient and effective response to emergencies. While 9-1-1 data is currently being collected across the nation, it is being used primarily for administrative purposes, not for real-time assessment and prediction of emergency response situations. This project will provide that linkage between the data and the spatiotemporal analysis techniques required to mine the data and develop predictive models. Impact - The project will involve first responders and emergency services personnel from State andlocal agencies, as well as representative personnel from border law enforcement information agencies,e.g. the Automated Regional Justice Information Systems (ARJIS), San Diego. Although the focus of thisproject is on California, PSN also has access to 9-1-1 call stream data across much of the U.S. Indeed, themethodologies developed in this research will be applicable immediately to other states and regions.

该奖项将支持加州圣地亚哥大学、加州州长紧急服务办公室（OES）和公共安全网络（PSN）公司之间的合作。目标是对9-1-1呼叫流数据进行时空分析，并将这些数据与外部事件相关联，以便在紧急情况下提供更有效和更高效的响应。 各种各样的现有和新出现的数据来源在帮助紧急情况办公室确定早期灾害的位置和规模方面具有潜在价值，及时获得这些数据对于紧急情况办公室管理国家一级的资源和协助地方政府向灾害受害者提供援助至关重要。PSN已与加州签订合同，收集全州的9-1-1呼叫流数据。PSN每天从数百个不同的公共安全报警点（PSAP）收集大约60- 80，000个紧急呼叫的数据。来自加州大学圣地亚哥分校圣地亚哥超级计算机中心和斯克里普斯海洋学研究所的研究人员将与PSN和OES合作，提供先进的数据管理，数据分析，数据挖掘和统计技术方面的专业知识，目标是对整个加州州的9-1-1紧急呼叫流数据进行时空分析，并将这些数据与外部信息相关联，例如地震和火灾。PSN将提供项目开始前4年内9-1-1呼叫流数据的档案数据集。分析将包括将这一信息与地震和野火等外部事件信息相关联，以确定这些事件的时空特征。然后，该信息将用于建立警报阈值，以向第一响应者和其他紧急服务人员提供关于紧急事件的空间范围和时间演变的预先警告。长期目标还包括利用这些信息实时检测紧急事件，以便在地方一级提供快速响应，并为州一级的资源分配和规划提供决策支持。智力优势-分析9-1-1呼叫流数据将更好地了解紧急呼叫的时空模式及其与外部事件的相关性。利用这些数据构建的预测模型可以提供实时决策支持和更好的整体规划，从而更有效地应对紧急情况。虽然9-1-1数据目前正在全国范围内收集，但它主要用于行政目的，而不是用于实时评估和预测紧急响应情况。该项目将提供数据与挖掘数据和开发预测模型所需时空分析技术之间的联系。影响-该项目将涉及来自州和地方机构的第一反应者和紧急服务人员，以及来自边境执法信息机构的代表人员，例如圣地亚哥的自动区域司法信息系统。尽管该项目的重点是加州，但PSN也可以访问美国大部分地区的9-1-1呼叫流数据。事实上，本研究中开发的方法论将立即适用于其他州和地区。