课题基金 / 基金详情

Spatiotemporal Analysis of 9-1-1 Call Stream Data

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:
$60.0万
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
项目状态:
已结题
起止时间:
2004-09-01 至 2008-08-31

项目摘要

项目成果

Chaitanya Baru的其他基金

相似基金

相关文献

中文摘要
翻译
该奖项将支持加州大学圣地亚哥分校、加利福尼亚州州长应急服务办公室(OES)和公共安全网络(PSN)公司之间的伙伴关系。目标是对911呼叫流数据进行时空分析,并将这些数据与外部事件关联起来,以便在紧急情况下提供更有效和高效的响应。各种各样的现有和新兴数据来源在帮助OES确定早期灾害的位置和规模方面具有潜在价值,及时获取这些数据对于OES管理国家级资源和协助地方政府向灾民提供援助至关重要。PSN已与加州签订合同,收集全州911呼叫流数据。PSN每天从数百个不同的公共安全应答点(PSAP)收集大约6 -8万个紧急呼叫的数据。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,目的是对加利福尼亚州的911紧急呼叫流数据进行时空分析,并将这些数据与外部信息(如地震和火灾)相关联。PSN将在项目开始前的4年期间提供911呼叫流数据的存档数据集。分析将包括这些信息与外部事件信息(如地震和野火)的相关性,以确定这些事件的时空特征。然后,这些信息将用于确定警报阈值,以便就紧急事件的空间范围和时间演变向第一响应者和其他紧急服务人员提供预警。长期目标还包括能够利用这些信息实时发现紧急事件,以便在地方一级作出快速反应,并促进在国家一级为资源分配和规划提供决策支持。智力优势——对911呼叫流数据的分析将有助于更好地理解紧急呼叫的时空模式及其与外部事件的相关性。利用这些数据建立的预测模型可以提供实时决策支持和更好的总体规划,从而更有效地应对紧急情况。虽然目前正在全国范围内收集911数据,但这些数据主要用于行政目的,而不是用于实时评估和预测紧急情况。该项目将提供数据与挖掘数据和开发预测模型所需的时空分析技术之间的联系。影响——该项目将涉及州和地方机构的急救人员和紧急服务人员,以及边境执法信息机构的代表人员,如:自动区域司法信息系统(ARJIS),圣地亚哥。虽然这个项目的重点是在加州,但PSN也可以访问美国大部分地区的911呼叫流数据。事实上,本研究中开发的方法将立即适用于其他州和地区。
英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
WBDB2012: Workshop on Big Data Benchmarking 2012
  • 批准号:
    1241838
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.5万
  • 财政年份:
    2012
  • 负责人:
    Chaitanya Baru
  • 依托单位:
Workshop on Cyberinfrastructure Platform for Public Health & Health Services, January 10 - 12, 2011
  • 批准号:
    1107514
  • 项目类别:
    Standard Grant
  • 资助金额:
    $3.5万
  • 财政年份:
    2010
  • 负责人:
    Chaitanya Baru
  • 依托单位:
Performance Evaluation of On-Demand Provisioning of Data Intensive Applications
  • 批准号:
    0844530
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.0万
  • 财政年份:
    2009
  • 负责人:
    Chaitanya Baru
  • 依托单位:
Geoinformatics: GEON 2.0: A Data Integration Facility for the Earth Sciences
  • 批准号:
    0744229
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $115.82万
  • 财政年份:
    2008
  • 负责人:
    Chaitanya Baru
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Intelligent Patent Analysis for Optimized Technology Stack Selection:Blockchain BusinessRegistry Case Demonstration
  • 批准号:
    --
  • 项目类别:
    外国学者研究基金项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    USHARANI HAREESH GOVINDARA JAN
  • 依托单位:
基于Meta-analysis的新疆棉花灌水增产模型研究
  • 批准号:
    41601604
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    22.0万元
  • 批准年份:
    2016
  • 负责人:
    赵爱琴
  • 依托单位:
大规模微阵列数据组的meta-analysis方法研究
  • 批准号:
    31100958
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2011
  • 负责人:
    赵洪雅
  • 依托单位: