The concept of multi-intelligence involves the use of diverse sources to gather information and insights, such as human intelligence, signals intelligence, geospatial intelligence, or open-source intelligence. However, an abundance of information can often lead to confusion and uncertainty, especially when trying to make critical decisions. Information fusion involves the correlation and integration of data from multiple sources to enhance situational awareness and support decision-making. Situational assessment is analysing a complex situation to gain a comprehensive understanding, while threat assessment is identifying and evaluating potential threats.
This document overviews thus more than 20 years of research on information fusion under uncertainty in a multi-intelligence context and highlights elements of diversity and unity that appear implicitly in these activities. Diversity of the sources of information, of information itself, of uncertainty, of uncertainty theories, of application domains, of scientific communities. Unity resulting from the discovery of links and commonality in formulation of measures, unity across the different levels of fusion, unity in knowledge representation, unity for generic formulations of fusion problems. We step back on some activities with an emphasis on the most recent ones, and report the main trends that can open to future research, to support defence and security applications and beyond.