Grant: Alliance Grants
Dalhousie University
$280,000.00
Automated Monitoring of the Naval Information Space (AMNIS)
EF 2021-22
Résumé
Modern defence organizations around the world face new challenges related to information flow. They deal with massive information streams from on-board sensors, coalitionpartners, or remote sites. This information needs to be absorbed and interpreted in its current decision-making context of time, space, and provenance. Such contextualization is known as Situational Awareness. The proposed AMNIS (Automated Monitoring of the Naval Information Space) project is an alliance of the Institute for Big Data Analytics at Dalhousie University (IBDA), the Atlantic Research Centre of the Defence Research and Development Canada (DRDC), and the General Dynamics (Mission Systems-Canada) group. AMNIS will bring the state-of-the-art data integration, modeling and predictive models to the task of Situational Awareness. AMNIS will build on the results and collaborative links established in the recent (2016-2019) IBDA-DRDC-Lockheed Martin Canada project on Mission-Relevant Information Management for Integrated Response (MIMIR). In AMNIS, we will use Machine Learning to address select SA aspects and learn the persistent alarm definitions from the data, to model the concepts of trust, to account for and reproduce doubtful provenance (adversarial) data, and to represent data drift. We will also develop techniques for data exploration and data-centered collaboration using visual queries and advanced data visualization. AMNIS will support more than 30 person-years of High- Quality Personnel training in Data Science, Machine Learning, and Data Visualization and advanced HCI -areas in high demand in the Canadian industrial and government labs.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Nova Scotia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
550722-2020
Name nom
Matwin, Stan
Department département
Computer Science, Faculty of
Organization id
79
Institution établissement
Dalhousie University
Province en
Nova Scotia
Province fr
Nouvelle-Écosse
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2021
Competition year année de concours
2020
Award amount
280000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
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
802
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 systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2805
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Learning and inference theories
Research subject fr
Théories de l'apprentissage et l'inférence
Installment
inst:2
Partie
1
Nb partie
3
Application title
Automated Monitoring of the Naval Information Space (AMNIS)
Keyword
NSERC
Application summary
Modern defence organizations around the world face new challenges related to information flow. They deal with massive information streams from on-board sensors, coalitionpartners, or remote sites. This information needs to be absorbed and interpreted in its current decision-making context of time, space, and provenance. Such contextualization is known as Situational Awareness. The proposed AMNIS (Automated Monitoring of the Naval Information Space) project is an alliance of the Institute for Big Data Analytics at Dalhousie University (IBDA), the Atlantic Research Centre of the Defence Research and Development Canada (DRDC), and the General Dynamics (Mission Systems-Canada) group. AMNIS will bring the state-of-the-art data integration, modeling and predictive models to the task of Situational Awareness. AMNIS will build on the results and collaborative links established in the recent (2016-2019) IBDA-DRDC-Lockheed Martin Canada project on Mission-Relevant Information Management for Integrated Response (MIMIR). In AMNIS, we will use Machine Learning to address select SA aspects and learn the persistent alarm definitions from the data, to model the concepts of trust, to account for and reproduce doubtful provenance (adversarial) data, and to represent data drift. We will also develop techniques for data exploration and data-centered collaboration using visual queries and advanced data visualization. AMNIS will support more than 30 person-years of High- Quality Personnel training in Data Science, Machine Learning, and Data Visualization and advanced HCI -areas in high demand in the Canadian industrial and government labs.