Plan-Driven Fusion: Shaping the Situation Awareness Process using Empirical Plan Data

DiBona, Phil; Belov, Nadya; Pawlowski, Angela

doi:10.1109/icif.2006.301669

Cited by 7 publications

(5 citation statements)

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“…Video analytics is one aspect of multi-intelligence fusion which incorporates sensor planning [14], resource management for situation assessment [15], geo-intelligence [16], and analyst support [17]. With a user work-domain environment, a primary function is to conduct pattern activity clustering and evaluation [18].…”

Section: Information Fusionmentioning

confidence: 99%

Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

Blasch

Waltz

2016

SPIE Proceedings

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Current analysts are inundated with large volumes of data from which extraction, exploitation, and indexing are required. A future need for next-generation analysts is an appropriate balance between machine analytics from raw data and the ability of the user to interact with information through automation. Many quantitative intelligence tools and techniques have been developed which are examined towards matching analyst opportunities with recent technical trends such as big data, access to information, and visualization. The concepts and techniques summarized are derived from discussions with real analysts, documented trends of technical developments, and methods to engage future analysts with multiintelligence services. For example, qualitative techniques should be matched against physical, cognitive, and contextual quantitative analytics for intelligence reporting. Future trends include enabling knowledge search, collaborative situational sharing, and agile support for empirical decision-making and analytical reasoning.

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Section: Information Fusionmentioning

confidence: 99%

Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

Blasch

Waltz

2016

SPIE Proceedings

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“…To the best of our knowledge, and as already mentioned, plan recognition has not received much attention in the Information Fusion community and very few works can be found. For example, it has been considered for a C4ISR 2 system in DiBona et al (2006). The authors present an architecture in which planning, monitoring, and information fusion modules cooperate in a closed-loop.…”

Section: Plan Recognition In Fusionmentioning

confidence: 99%

“…As discussed in Sect. 14.5.1, this process is described in DiBona et al (2006). This process would be followed by the planning step (next point) to properly cue sources to gather the relevant context and information needed to accomplish the user's goals.…”

Section: Plan Recognition and Sa For Crisis Managementmentioning

confidence: 99%

Network Methods and Plan Recognition for Fusion in Crisis Management

Snidaro

Visentini

2016

Fusion Methodologies in Crisis Management

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Building and updating a situational picture of the scenario under consideration is the goal of the Situation Assessment (SA) Information Fusion (IF) process. The scenario generally involves multiple entities and actors where possibly only a few under direct control of the decision maker. SA aims at explaining the observed events (mainly) by establishing the entities and actors involved, inferring their goals, understanding the relations existing (whether permanently or temporarily) between them, the surrounding environment, and past and present events. It is therefore apparent how the SA process inherently hinges on understanding and reasoning about relations. SA is a necessary preparatory step to the following phase of Impact Assessment (IA) where the decision maker is interested in estimating the evolution of the situation and the possible outcomes, dangers and threats. SA and IA processes are particularly complex and critical for large-scale scenarios with nearly chaotic dynamics such as those affected by natural or man-made disasters. This chapter will discuss recent developments in information fusion methods for representing and reasoning about relational information and knowledge for event detection in the context of crisis management. In particular, network methods will be analysed as a means for representing and reasoning about relational knowledge with the purpose of detecting complex events or discovering the causes of observed evidence.

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“…Recent information fusion techniques include big data analytics (Blasch, Steinberg, et al, 2013). Multimedia analytics includes multiintelligence fusion from which we seek sensor planning (DiBona, et al, 2006), resource management for situation assessment (Blasch, et al, 2008), geo-intelligence (Blasch, Deignan, et al, 2011), and analyst support . With a user work-domain environment, a QuEST application is situational activity-based intelligence (ABI) (Blasch, Banas, et al, 2012).…”

Section: Information Fusionmentioning

confidence: 99%

QuEST for Information Fusion in Multimedia Reports

Blasch

Rogers

Holloway

et al. 2014

International Journal of Monitoring and Surveillance Technologies Research

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Qualia-based Exploitation of Sensing Technology (QuEST) is an approach to create a cognitive exoskeleton to improve human-machine decision quality. In this paper, the authors present QuEST-motivated man-machine information fusion with an example for multimedia narratives. User-based situation awareness includes both elements of external sensory perception and internal cognitive explanation. The authors outline QuEST elements and tenets towards a reasoning approach that achieves human intelligence amplification (IA) in relation to data aggregation from machine artificial intelligence (AI). In a use case example for multimedia exploitation, they showcase the need for enhanced understanding of the man (mind-body cognition) and the machine (sensor-based reasoning) for establishing a cohesive narrative of situational activities. QuEST tenets of structurally coherent, situated conceptualization, and simulated experience are utilized in organizing multimedia reports of Video Event Segmentation by Text (VEST).

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Plan-Driven Fusion: Shaping the Situation Awareness Process using Empirical Plan Data

Cited by 7 publications

References 0 publications

Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

Network Methods and Plan Recognition for Fusion in Crisis Management

QuEST for Information Fusion in Multimedia Reports

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