Grant: Department of National Defence / NSERC Research Partnership

This project aims to develop a functional context-aware case-based reasoning system by enhancing the current intelligence capability of Canadian Defence with a nexus of technologies and processes, including software modelling and simulation, meta-level modelling and reasoning, and psycho-physiological modelling and monitoring, which together will deliver a powerful future intelligence analysis capability. The central objective is to support intelligence analysts during the collection and processing phases of the intelligence cycle through load minimization and improved human-machine synergy. This involves sense-making from both explicit and implicit contextual information about the element-of-interest for the analyst, as well as monitoring the analyst's internal states to adapt the delivery of information accordingly. The complete system involves a combination of humans and software agents operating on event data and situation context to deliver an effective intelligence analysis system. The human analyst is central to the system for seeing patterns in data, understanding unfolding events and situations, and recommending courses of action to decision-makers or policy-makers. In terms of capabilities, 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 for the Canadian Forces, but also for a wider range of stakeholders, including the fields of emergency response and hospital operations. This will save lives and increase the safety and security of Canadians and will allow Canada to play a leading role in developing synergistic, human-machine systems and would also result in the training of highly qualified personnel.