In order to achieve effective and efficient reconnaissance to meet military information requirements, the use of modern and innovative technical tools is essential. The processes established in the Austrian Armed Forces for military reconnaissance are based on the standardized NATO Intelligence Cycle and
provide the basis for the automation of digital processing. The main objective of PIONEER is to analyse and document requirements for an interoperable information system for automated processing in the reconnaissance process, to model the processes behind it and to compare different architectures.

In addition, performance metrics were to be defined to evaluate the performance of a possible future reconnaissance information system. The project investigates and identifies artificial intelligence methods from the domains of, e.g., NLP (text analysis), computer vision (image processing) and knowledge modelling that can be usefully applied for automation in the reconnaissance process.

In particular, the focus of the prototypical functions is to support analysts in evaluating the messages sent by the sensors, recognizing patterns, and drawing conclusions. To this end, modern AI approaches should be used to automatically generate suggestions - such as text and object recognition in images, terms extracted from texts, and relationships. Different views of the data - georeferenced in a map, as a time-event diagram, or as a network of relationships - should provide the most comprehensive overview possible.