Emulating the Perceptual System of the Brain for the Purpose of Sensor Fusion

Abstract

-This work presents a bionic model derived from research findings about the perceptual system of the human brain to build next generation intelligent sensor fusion systems. Therefore, a new information processing principle called neuro-symbolic information processing is introduced. According to this method, sensory data are processed by so-called neuro-symbolic networks. The basic processing units of neuro-symbolic networks are neurosymbols. Correlations between neuro-symbols of a neurosymbolic network can be learned from examples. Perception is based on sensor data as well as on interaction with cognitive processes like focus of attention, memory, and knowledge. Additionally, a mechanism for evaluating perception by emotions is suggested.

Neurosymbolic Alerting Rules

“…To do so, buildings will have to be equipped with a large number of diverse sensors, whose information has to be merged in order to get a robust representation of the environment, as studied in sensor fusion [3]. However, this research field is still quite recent and existing approaches are challenged by this abundance of data and the ways in which it should be analyzed and responded to [4], [5]. There is thus a need for new concepts to handle future demands [6].…”

Knowledge representation for a neuro-symbolic network in home care risk identification

“…New methods and information processing principles are needed to handle these demands of the upcoming future. In recent times, research started to focus on bionic principles looking at nature as an archetype [3]. In fact, animals and humans are themselves equipped with millions of sensory receptors.…”