Cognitive Ergonomics In Sustainable Systems: Bridging The Gap Between Visual Perception Theory And Real-Time Carbon Emission Monitoring

Abstract

Background: As global industries pivot toward carbon neutrality, the volume of environmental data generated by Cyber-Physical Systems (CPS) has grown exponentially. However, the efficacy of this data is frequently compromised by poor visual presentation, leading to high cognitive load and suboptimal decision-making.

Methods: This study employs a multidisciplinary review, synthesizing literature from cognitive psychology, visual perception science, and environmental engineering. We analyze existing frameworks for carbon emission monitoring in pre-fabricated construction, smart logistics, and residential energy systems against established principles of visual data communication, such as aspect ratio bias and the "curse of knowledge."

Results: The analysis indicates that traditional engineering dashboards often prioritize data completeness over human intelligibility. We find that simplified visual encodings, optimized for pre-attentive processing, significantly correlate with improved user reaction times in energy management scenarios. Furthermore, the integration of AI-driven data repair techniques and knowledge graphs enhances the reliability of the underlying data presented.

Conclusion: We conclude that sustainable systems must adopt "Cognitive Ergonomics" as a core design principle. By aligning dashboard design with human perceptual limitations, organizations can transform raw emission data into actionable insights, thereby accelerating the transition to sustainable energy paradigms.