Rearchitecting Human–Computer Interaction: The Rise of Spatial Intelligence Systems
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V4I4P115Keywords:
Spatial Computing, Human–Computer Interaction, Spatial Intelligence Systems, Extended Reality (XR), Edge Computing, Internet of Things (IoT), Metaverse Architecture, Immersive SystemsAbstract
Human–computer interaction (HCI) is undergoing a structural transformation as computing systems evolve from screen-bound interfaces to spatially aware, intelligent environments. Traditional interaction paradigms centered on keyboards, touchscreens, and graphical user interfaces are increasingly inadequate for emerging immersive and distributed ecosystems. This paper introduces the concept of Spatial Intelligence Systems (SIS) as a unifying architectural framework that integrates augmented reality, deep learning–driven perception, Internet of Things (IoT) infrastructures, edge computing, and metaverse-scale virtual environments. Unlike conventional AR/VR systems that primarily focus on visualization and rendering, SIS are defined as AI-driven computational ecosystems capable of perceiving, interpreting, and interacting with physical environments in real time through multimodal sensing and immersive feedback mechanisms. The paper presents a layered systems architecture encompassing spatial sensing, edge-based inference, scene understanding, immersive interaction, and governance layers. Through a cross-domain analysis spanning healthcare, manufacturing, and smart environments, this study demonstrates how spatial intelligence reshapes interaction from device-centric control to environment-centric cognition. Key technical challenges are examined, including latency constraints, distributed inference, scalability, interoperability, adversarial robustness, and privacy risks in immersive systems. Ethical implications surrounding biometric profiling and pervasive data collection are also addressed, emphasizing the need for privacy-preserving and secure spatial AI frameworks. By recontextualizing spatial computing as an architectural shift rather than a hardware evolution, this work contributes a systems-level perspective that bridges artificial intelligence, extended reality, and distributed computing. The paper concludes by outlining future research directions toward adaptive, secure, and human-centric spatial intelligence ecosystems.
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