Autonomous Perception and Decision Making in Building Automation

Abstract

System complexity has reached a level where it is hard to apply existing information analysis methods to automatically derive appropriate decisions. Building automation is on the verge of being unable to extract relevant information and control a building accordingly. Many different industries in today's automation could provide information by means of different sensors, but the ability to integrate this information is missing. This paper describes approaches on how to cope with increased complexity by introducing models for perception and decision making that are based on findings in neuroscience and psychoanalysis, scientific disciplines that are far-off from engineering but nevertheless promise valuable contributions to intelligent automation.