Conversational control interface to facilitate situational understanding in a city surveillance setting

Abstract

In this paper we explore the use of a conversational interface to query a decision support system providing information relating to a city surveillance setting. Specifically, we focus on how the use of a Controlled Natural Language (CNL) can provide a method for processing natural language queries whilst also tracking the context of the conversation with relation to past utterances. Ultimately, we propose our conversational approach leads to a versatile tool for providing decision support with a low enough learning curve such that untrained users can operate it either within a central command location or when operating within the field (at the tactical edge). The key contribution of this paper is an illustration of applied concepts of CNLs as well as furthering the art of conversational context tracking whilst using such a technique.