Smart Nodes for Semantic Analysis of Visual and Aural Data

This paper proposes a system architecture that uses smart adaptive wireless networks of embedded sensing components to automatically detect uncommon or dangerous situations. The transformation of sensor values to semantic concepts enables the system to recognize predefined situation recognition and create a consistent world model between the nodes. It supports human operators of surveillance system and brings existing CCTV systems to the next level of machine-supported scenario detection.