An integrated approach to high-level information fusion

Sycara, Katia; Glinton, Robin; Yu, Bin; Giampapa, Joseph; Owens, Sean; Lewis, Michael; Grindle, Ltc Charles

doi:10.1016/j.inffus.2007.04.001

Cited by 40 publications

(32 citation statements)

References 41 publications

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“…However, Table 1 shows how, save for [112] which presents a framework for the inclusion of CI in high-level fusion processes (Levels 2-4), all the works focus on a specific fusion process and provide a solution which applies only to specific functions. Most examples are in fact tailored to the characteristic of the problems addressed instead of general processes to design context-integrated fusion systems.…”

Section: Context In Fusionmentioning

confidence: 99%

“…Since the cooperation and sharing interactions may not be predefined a priori, this leads to requirements for semanticbased agent discovery, with a service overlay approach. Sycara et al [129] propose the HiLIFE (High-Level Information Fusion Environment) fusion model for battlefield management. To these authors, context is defined as significant features that influence a situation, or expectations on what is to be observed and the interpretation of what has been observed.…”

Section: Situation Assessmentmentioning

confidence: 99%

“…In a framework that encompasses different high-level fusion processes (JDL Levels 2-4), a model for inferring adversary intent by mapping sensor readings of opponent forces to possible opponent goals and actions is presented in [112]. In addition to extending concepts developed earlier for the use of context in intelligence processing [110], where context is seen as being able to influence the value of a situational feature of interest, context is also considered ''source of expectations of what is to be observed and interpretation of what has been observed''.…”

Section: Intent Assessmentmentioning

confidence: 99%

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Context-based Information Fusion: A survey and discussion

2015

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This survey aims to provide a comprehensive status of recent and current research on context-based Information Fusion (IF) systems, tracing back the roots of the original thinking behind the development of the concept of ''context''. It shows how its fortune in the distributed computing world eventually per-meated in the world of IF, discussing the current strategies and techniques, and hinting possible future trends. IF processes can represent context at different levels (structural and physical constraints of the scenario, a priori known operational rules between entities and environment, dynamic relationships modelled to interpret the system output, etc.). In addition to the survey, several novel context exploita-tion dynamics and architectural aspects peculiar to the fusion domain are presented and discussed.

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Section: Context In Fusionmentioning

confidence: 99%

Section: Situation Assessmentmentioning

confidence: 99%

Section: Intent Assessmentmentioning

confidence: 99%

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Context-based Information Fusion: A survey and discussion

2015

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“…terrain), existing reports and databases, and so forth [25,26]. Sycara et al state that part of the context are the significant features or the history of a situation that influence the features of other situation, as well as the expectations on what is to be observed and the interpretation of what has been observed [27]. They also propose the HiLIFE (High-Level Information Fusion Environment) fusion model for battlefield management.…”

Section: Context Definition and Representationmentioning

confidence: 99%

“…The specific contents of the context model for the harbor surveillance problem are described in Section 3. Context can thus be used to explain observations, to define hypotheses, to identify areas of interest to focus new data collection, to refine ambiguous estimations, and to provide for interrelationship between different fusion levels [27,28].…”

Section: Context Definition and Representationmentioning

confidence: 99%

Context-based multi-level information fusion for harbor surveillance

et al. 2015

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Abstract:Harbor surveillance is a critical and challenging part of maritime security procedures. Building a surveil-lance picture to support decision makers in detection of potential threats requires the integration of data and information coming from heterogeneous sources. Context plays a key role in achieving this task by providing expectations, constraints and additional information for inference about the items of interest. This paper proposes a fusion system for context-based situation and threat assessment with application to harbor surveillance. The architecture of the system is organized in two levels. The lowest level uses an ontological model to formally represent input data and to classify harbor objects and basic situations by deductive reasoning according to the harbor regulations. The higher level applies Belief-based Argumen-tation to evaluate the threat posed by suspicious vessels. The functioning of the system is illustrated with several examples that reproduce common harbor scenarios. IntroductionMaritime security is an area of strategic importance for the international community. As stated in [1], ''a terrorist incident against a marine transportation system would have a disaster impact on global shipping, international trade, and the world economy in addition to the strategic military value of many ports and waterways''. For that reason, one of the principal goals of strengthening maritime security is to ''increase maritime domain awareness'' by building a ''surveillance picture as complete as possible to assess the threats and vulnerabilities in the maritime realm''. In particular, harbor surveillance is a critical part of maritime security procedures because of its multiple objectives: recognition of terrorist threats, prevention of maritime and ecological accidents, detection of illegal immigration, fishing and drug trafficking, and so forth. However, it is nowadays mostly developed by human operators [2], who have to evaluate an overwhelming amount of information. This makes it very difficult to keep track of the event stream with the required level of attention due to distraction, fatigue and oversight. In addition, their decisions may be strongly affected by sensor data imprecision and subjective judgment. make informed decisions. According to the JDL data fusion model, the latter task belongs to the domain of Situation Assessment, defined as the estimation of ''sets of relationships among entities and their implications for the states of the related entities '' [4]. In this domain, it requires understanding the intrinsic information provided by coastal sensors in the context determined by extrinsic factors, like harbor environment, operational regulations, traffic data and intelligence reports.Recently, the increasing interest in higher-level information fusion has led to several proposals for context management -see for example the special sessions on context-based information fusion celebrated in the International Conferences on Information Fusion since 2007. Detection and characteri...

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Cooperative situation assessment in a maritime scenario

Farinelli

Nardi

Pigliacampo³

et al. 2012

Int. J. Intell. Syst.

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In large-scale, complex domains such as space defense and security systems, situation assessment and decision making are evolving from centralized models to high-level, net-centric models. In this context, collaboration among the many actors involved in the situation assessment process is critical in order to achieve a prompt reaction as needed in the operational scenario.In this paper, we propose a multi-agent based approach to situation assessment, where agents cooperate by sharing local information to reach a common and coherent assessment of situations. Specifically, we characterize situation assessment as a classification process based on OWL ontology reasoning, and we provide a protocol for cooperative multi-agent situation assessment, which allows the agents to achieve coherent high level conclusions. We validate our approach in a real maritime surveillance scenario, where our prototype system effectively supports the user in detecting and classifying potential threats; moreover, our distributed solution performs comparably to a centralized method, while preserving independence of decision makers and dramatically reducing the amount of communication required.

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An integrated approach to high-level information fusion

Cited by 40 publications

References 41 publications

Context-based Information Fusion: A survey and discussion

Context-based Information Fusion: A survey and discussion

Context-based multi-level information fusion for harbor surveillance

Cooperative situation assessment in a maritime scenario

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