Cognitive System
- 01 / Architecture
Layered construct
Nomon’s architecture is a layered system that uses perception to analyze data. Environmental and human signals are collected, integrated into specific constructs, and aligned into perceptual structures through cognitive gravity.
Each layer combines human cognitive principles and AI processing, generating decision layers that enable environments to adapt, predict, and evolve around cognitive variables.
- 02 / Perception
Geometry of Perception
The human dimension draws on cognitive geometry, neurogeometry, and geometric cognition. Perception is the driver of geometric relations between signals. Neural operations such as symmetry and topology detection provide biological grounding, while spatial metaphors extend cognition into reasoning and language. These principles justify perception as the system’s integrative core.
- 03 / Processing
Machine Extension of Cognition
AI processing in Nomon mirrors human cognition at computational scale. Neuromorphic systems emulate neural dynamics for real-time sensory data.
Geometric deep learning embeds signals into graphs and manifolds, detecting relational invariants. Data science ensures robustness through multimodal fusion and probabilistic modeling.
Together, these enable adaptive, predictive environments where human and machine cognition converge.
- 04 / Standards
Interoperable by Design
Nomon integrates cognitive variables within established frameworks such as Brick Schema, Real Estate Core, and ASHRAE 223P. By aligning with these standards, cognitive structures can be layered into existing infrastructures without disruption.
This compatibility ensures interoperability, reduces integration risk, and provides a pathway toward sector-wide adoption while defining cognition as a new domain in building intelligence.
