On-the-fly integration of soft and sensor data for enhanced situation assessment

Abstract

Situation assessment is at the core of many critical tasks in the civilian and military domains: border monitoring, surveillance of areas and facilities, entity tracking and identification, all require accurate and up-to-day descriptions of the course of events. For all those applications, situations to be built are complex, dynamic and uncertain and their assessment is based on the integration of diverse sources, including sensors and their row values, images, observations, tactical information and knowledge expressed by domain experts or synthesized through discovery techniques. This paper presents a method to combine soft and sensor data to create enhanced situation assessment for a track-and-detect application. First we create a situation of entities and relationships by using only hard data provided by sensors and then we enrich this situation thanks to soft data, in the form of succinct or more complex observation reports. The system relies on semantic mediation to combine observations and sensor data by using ontologies as a common ground creating a bridge between two complementary yet incomplete representations of the world. The result is an augmented situation, having more precise, accurate or complete descriptions of entities and which is easier to analyze. This enhanced assessment allows for the situation to be understood and processed in a meaningful way by decision makers.