Publications and Research
Document Type
Report
Publication Date
4-27-2026
Abstract
This report presents the system architecture for the Self-Aware Room, an evolvable research platform designed to transform heterogeneous environmental signals into structured semantic representations for decision-making, simulation, and immersive media output. The architecture is organized as a layered mediation pipeline, beginning with raw data acquisition from diverse sensing modalities and proceeding through local processing, feature abstraction, cross-modal fusion, semantic interpretation, and output to digital twin and immersive audiovisual systems. Rather than defining the system through a fixed set of devices, the report emphasizes the transformation pathways by which sensor data becomes computationally tractable, interpretable, and actionable. The architecture also allows for asynchronous computational extensions, including quantum processing pathways, as complementary interpretive processes rather than real-time control mechanisms. Overall, the Self-Aware Room is framed as both an engineered environment and a research framework for investigating how meaning and action emerge from complex mediated interactions among physical signals, computational models, and interpretive systems.
Comments
The Self-Aware Room meta-project as part of a broader research program investigating Balanced Blended Space and collaborative AI. It is intended to serve as a citable technical reference for subsequent conceptual, practical, and theoretical work on blended environments, digital twins, semantic transformation, and human-AI collaboration. It also establishes the architectural foundation for the detailed specification and instantiation of the Self-Aware Room currently underway (2026) in the Center for Holistic Integration at New York City College of Technology. Supporting project materials and ongoing implementation documentation are available in the related GitHub repository: https://github.com/CHI-CityTech/Self-Aware-Room