Grant: Department of National Defence / NSERC Research Partnership
Carleton University
$45,000.00
RECON: Context-Aware Case-Based Reasoning for the Intelligence Virtual Analyst Capability (iVAC)
FY 2013-14
Summary
This project aims to develop a functional context-aware case-based reasoning system by enhancing the currentintelligence capability of Canadian Defence with a nexus of technologies and processes, including softwaremodelling and simulation, meta-level modelling and reasoning, and psycho-physiological modelling andmonitoring, which together will deliver a powerful future intelligence analysis capability. The central objectiveis to support intelligence analysts during the collection and processing phases of the intelligence cycle throughload minimization and improved human-machine synergy. This involves sense-making from both explicit andimplicit contextual information about the element-of-interest for the analyst, as well as monitoring the analyst'sinternal states to adapt the delivery of information accordingly. The complete system involves a combination ofhumans and software agents operating on event data and situation context to deliver an effective intelligenceanalysis system. The human analyst is central to the system for seeing patterns in data, understanding unfoldingevents and situations, and recommending courses of action to decision-makers or policy-makers. In terms ofcapabilities, the outcomes include the following:- An intelligence analysis system incorporating natural interfaces between analysts and system agents- A context-sensitive reasoning system based on multidimensional models and real-time data- A brain-monitoring system capable of recognizing features such as relevance and workload- Research and development (designs and proof-of-concept)These project outcomes have the potential to improve the current intelligence analysis capability, not only forthe Canadian Forces, but also for a wider range of stakeholders, including the fields of emergency response andhospital operations. This will save lives and increase the safety and security of Canadians and will allowCanada to play a leading role in developing synergistic, human-machine systems and would also result in thetraining of highly qualified personnel.
Program
Department of National Defence / NSERC Research Partnership
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
444871-2012
Name nom
DAngiulli, Amedeo
Department département
Neuroscience, Institute of
Organization id
23
Institution établissement
Carleton University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2013
Competition year année de concours
2012
Award amount
45000
Program id
DNDPJ
Program name en
Department of National Defence / NSERC Research Partnership
Program name fr
Partenariat de recherche du ministère de la Défense nationale et du CRSNG
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
800
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information and communication services
Area of application fr
Services d'information et de télécommunications
Research subject code
2717
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Modelling and simulation studies
Research subject fr
Études de modélisation et de simulation
Partie
2
Nb partie
2
Application title
RECON: Context-Aware Case-Based Reasoning for the Intelligence Virtual Analyst Capability (iVAC)
Keyword
NSERC
Application summary
This project aims to develop a functional context-aware case-based reasoning system by enhancing the currentintelligence capability of Canadian Defence with a nexus of technologies and processes, including softwaremodelling and simulation, meta-level modelling and reasoning, and psycho-physiological modelling andmonitoring, which together will deliver a powerful future intelligence analysis capability. The central objectiveis to support intelligence analysts during the collection and processing phases of the intelligence cycle throughload minimization and improved human-machine synergy. This involves sense-making from both explicit andimplicit contextual information about the element-of-interest for the analyst, as well as monitoring the analyst'sinternal states to adapt the delivery of information accordingly. The complete system involves a combination ofhumans and software agents operating on event data and situation context to deliver an effective intelligenceanalysis system. The human analyst is central to the system for seeing patterns in data, understanding unfoldingevents and situations, and recommending courses of action to decision-makers or policy-makers. In terms ofcapabilities, the outcomes include the following:- An intelligence analysis system incorporating natural interfaces between analysts and system agents- A context-sensitive reasoning system based on multidimensional models and real-time data- A brain-monitoring system capable of recognizing features such as relevance and workload- Research and development (designs and proof-of-concept)These project outcomes have the potential to improve the current intelligence analysis capability, not only forthe Canadian Forces, but also for a wider range of stakeholders, including the fields of emergency response andhospital operations. This will save lives and increase the safety and security of Canadians and will allowCanada to play a leading role in developing synergistic, human-machine systems and would also result in thetraining of highly qualified personnel.
