Santosh Dawesar, Daniel Jennings, Piali De, Brian C. Urch, Scott Corwin, Peter T Gaynor
{"title":"Providing decision support in complex missions such as responding to a metropolitan IED attack","authors":"Santosh Dawesar, Daniel Jennings, Piali De, Brian C. Urch, Scott Corwin, Peter T Gaynor","doi":"10.1109/THS.2010.5655054","DOIUrl":null,"url":null,"abstract":"Responding to a terrorist attack is extraordinarily complex due to the unpredictability as well as the resulting devastation, confusion, and apprehension. Further complications arise from the enormity of available data as well as the participation of multiple agencies and organizations, which often hinders the discovery and assimilation of pertinent information in a timely fashion. A solution to these problems must be scalable, maintainable, extensible, and adaptable. Increasingly, decision-makers need an integrated, intelligent system that can seamlessly acquire, fuse, reason about, distribute, and protect information to provide enhanced, individualized decision support and situational understanding as well as foster effective collaboration. To meet this need, Raytheon is developing an intelligent system called Confluence™, which consists of an ontological framework, domain independent knowledge generation, integration, and reasoning agents, a massively scalable knowledge store, as well as various visualization components. Confluence™ can be applied to any mission by creating a mission ontology that extends the common framework, and which explicitly defines a semantic model of the physical, information, cognitive, and social domains for the mission. This paper will describe and demonstrate an application of Confluence™ to the mission of recovering from an IED attack in a crowded metropolitan area, such as Providence RI.","PeriodicalId":106557,"journal":{"name":"2010 IEEE International Conference on Technologies for Homeland Security (HST)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Technologies for Homeland Security (HST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/THS.2010.5655054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Responding to a terrorist attack is extraordinarily complex due to the unpredictability as well as the resulting devastation, confusion, and apprehension. Further complications arise from the enormity of available data as well as the participation of multiple agencies and organizations, which often hinders the discovery and assimilation of pertinent information in a timely fashion. A solution to these problems must be scalable, maintainable, extensible, and adaptable. Increasingly, decision-makers need an integrated, intelligent system that can seamlessly acquire, fuse, reason about, distribute, and protect information to provide enhanced, individualized decision support and situational understanding as well as foster effective collaboration. To meet this need, Raytheon is developing an intelligent system called Confluence™, which consists of an ontological framework, domain independent knowledge generation, integration, and reasoning agents, a massively scalable knowledge store, as well as various visualization components. Confluence™ can be applied to any mission by creating a mission ontology that extends the common framework, and which explicitly defines a semantic model of the physical, information, cognitive, and social domains for the mission. This paper will describe and demonstrate an application of Confluence™ to the mission of recovering from an IED attack in a crowded metropolitan area, such as Providence RI.