The Reference Architecture

From Signals to Experiences: A Unified Semantic Topology

The Fragmentation Challenge

Current multisensory systems operate on a "peripheral model." A VR headset renders light; a haptic vest renders vibration; an olfactory dispenser releases chemical bursts. These devices have no shared understanding of the reality they are trying to simulate.

The Result: Sensory Dissonance

If a user sees a virtual fire but the thermal feedback lags by 200ms, or the smell of smoke persists after the fire is extinguished, immersion is broken and cognitive load increases.

The Solution

Sensora-OS inverts this model. Instead of applications driving devices directly, they drive the Experience Operating System, which orchestrates the hardware to maintain a cohesive sensory state.

Sensora-OS: The Unified Platform

Sensora-OS Platform Architecture

Core Architecture Components

Component 1

The Experience Graph (Gexp)

At the kernel level, Sensora-OS does not process "video" or "audio" files. It processes Experience Graphs.

An Experience Graph is a directed acyclic graph (DAG) where:

  • Nodes represent unified Sensory States (a snapshot of vision, sound, haptics, taste, and smell at time t)
  • Edges represent Transitions driven by time, user interaction, or biometric feedback

This allows the OS to "look ahead" and pre-load chemical cartridges or pre-tension haptic actuators, ensuring perfect synchronization.

Experience Graph Flow

Figure: Sensory data flows from the brain through the Experience Graph to distributed hardware endpoints

Component 2

The Personal Sensory Profile (PSP)

Unlike a standard OS, Sensora-OS interacts directly with human physiology. This requires a dedicated safety kernel known as the Personal Sensory Profile (PSP).

The PSP acts as a "biological firewall" between the application and the user. It enforces:

  • Intensity Ceilings: Hard limits on decibels, lumens, and haptic force based on the user's age and health
  • Chemical Gating: Preventing the release of specific allergens (e.g., peanut derivatives in a scent module) based on medical data
  • Cognitive Load Management: Monitoring biometric stress levels to dynamically dampen sensory input if the user becomes overwhelmed
Safety Research

Continuous biometric monitoring ensures user safety

Component 3

The Multisensory Hardware Abstraction Layer (HAL)

Sensora-OS is hardware-agnostic. It uses a standard Hardware Abstraction Layer (HAL) to translate high-level experience commands into device-specific machine code.

Hardware Abstraction

The HAL bridges software and diverse hardware platforms

Hardware Device Classification

We categorize sensory endpoints into five primary classes:

Vision Icon

Class V: Vision

AR/VR Headsets & Smart Glasses

Reference: Sensora VISTA

Audio Icon

Class A: Audio

Spatial Audio Emitters & Bone Conduction

Reference: Sensora AURIS

Touch Icon

Class H: Haptics

Vibrotactile Suits, E-Skin, & Thermal Weaves

Reference: Sensora HAPTI

Olfaction Icon

Class O: Olfaction

Micro-fluidic Scent Dispensers

Reference: Sensora AROMA

Gustation Icon

Class G: Gustation

Digital Taste Actuators

Reference: Sensora GUSTO

Deep Dive

For the mathematical formalism of the Experience Graph and the API specifications for the HAL,
please consult the full reference document.

Download Technical Specification (PDF)