QuEST for Information Fusion in Multimedia Reports

2015

SPIE Proceedings

Assessment of multi-intelligence fusion techniques includes credibility of algorithm performance, quality of results against mission needs, and usability in a work-domain context. Situation awareness (SAW) brings together low-level information fusion (tracking and identification), high-level information fusion (threat and scenario-based assessment), and information fusion level 5 user refinement (physical, cognitive, and information tasks). To measure SAW, we discuss the SAGAT (Situational Awareness Global Assessment Technique) technique for a multi-intelligence fusion (MIF) system assessment that focuses on the advantages of MIF against single intelligence sources. Building on the NASA TLX (Task Load Index), SAGAT probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points; we highlight these tools for use in a Multi-Intelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measures of product quality and QuEST of information. Building a notion of product quality from multiintelligence tools is typically subjective which needs to be aligned with objective machine metrics.

Section: Discusssionmentioning

confidence: 99%

Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT)

2015

SPIE Proceedings

“…MiCRAFT also seeks to measure Qualia-based Exploitation of Sensing Technology (QuEST) from multi-intelligence tools as sensing as a service (SaSS) to users [110,111]. QuEST seeks a new set of multi-intelligence processes that will be implemented in a computer agent (or set of computer agents) to improve decision quality of a human agent (or set of human agents).…”

Section: B Quest For Information Analysismentioning

confidence: 99%

Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT) method

2015 National Aerospace and Electronics Conference (NAECON)

2015

Assessment of multi-intelligence fusion techniques includes algorithm performance credibility, mission needs quality assessment, and work-domain usability. Situation awareness (SAW) bridges low-level information fusion (tracking and identification), with high-level information fusion (threat and scenario-based assessment), against user refinement (physical, cognitive, and information tasks). To measure SAW, common techniques include the NASA TLX (Task Load Index), SAGAT (Situational Awareness Global Assessment Technique) probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points. These SAW tools are combined for a MultiIntelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measure SAW in the QuEST of information.

“…Big data includes the management and analysis of various types of information available from controlled platforms such as radar [75], electro-optical sensors [76,77], target tacking [78,79,80,81], and sensor management [82], as well as uncontrolled sources such as multi-media [83]. The notion of "swimming in sensors and drowning in data" requires new methods for data analytics that can support C2.…”

Section: Big Datamentioning

confidence: 99%

Agile battle management efficiency for command, control, communications, computers and intelligence (C4I)

Signal Processing, Sensor/Information Fusion, and Target Recognition XXV

Bélanger

2016

Various operations such as civil-military co-operation (CIMIC) affairs require orchestration of communications, assets, and actors. A key component includes technology advancements to enable coordination among people and machines the ability to know where things are, who to coordinate with, and open and consistent lines of communication. In this paper, we explore concepts of battle management (BM) to support high-tempo emergency response scenarios such as a disaster action response team (DART). Three concepts highlighted of agile battle management (ABM) include source orchestration (e.g., sensors and domains), battle management language (BML) development (e.g., software and ontologies), and command and control (C2) coordination (e.g., people and visualization); which require correlation and de-confliction. These concepts of ABM support the physical, information, and cognitive domains for efficient command, control, communications, and information (C3I) to synchronize data and people for efficient and effective operations.