The Portals Lab

K01

Modular Sensor Server Architecture

Separating sensing, spatial processing, communication, and real-time media into reusable system layers.

A modular architecture for interactive environments that separates sensor acquisition and spatial processing from real-time media systems. The approach allows LiDAR, depth cameras, Raspberry Pi edge nodes, OSC, TouchDesigner, Unity, and other components to evolve independently while maintaining a reusable interaction pipeline across installations and research environments.

K02

Scene-Based Interaction

Structuring responsive environments as spatial states and scenes that translate human activity into coherent media behaviour.

A scene-based interaction model for responsive environments that separates sensing from experience behaviour. Spatial observations such as presence, position, area activation, and interaction events are interpreted as states that control scenes, transitions, media layers, and system responses. The approach supports clearer interaction logic, reusable experience structures, and more manageable multi-zone installations.

K03

Raw Sensor Data to Interaction Data

Transforming continuous LiDAR and depth-sensing measurements into stable spatial observations, interaction states, and research-ready data.

A technical framework for transforming raw spatial sensor measurements into meaningful interaction data for responsive environments. The pipeline separates acquisition, filtering, coordinate transformation, spatial fusion, tracking, area detection, event generation, and research logging so that LiDAR and depth-camera systems can provide reusable spatial observations to real-time experience applications.

K04

Spatial Interaction Logging & Session Architecture

Structuring session identity, trajectories, interaction events, dwell time, and synchronized logs for research-ready responsive environments.

A research-oriented logging architecture for responsive environments that organizes continuous spatial tracking, discrete interaction events, experience states, and system observations around a shared session identity. The approach supports trajectory reconstruction, dwell-time analysis, interaction counts, heatmaps, and cross-system synchronization while keeping research instrumentation separate from real-time experience logic.

K05

Multi-Sensor Spatial Fusion & Coordinate Calibration

Transforming observations from multiple spatial sensors into a shared room coordinate system for robust tracking, interaction detection, and research logging.

A technical framework for calibrating and combining spatial observations from multiple LiDAR and depth sensors within responsive environments. The architecture transforms sensor-local measurements into a shared room coordinate system, manages overlapping observations and occlusion, and produces stable fused spatial estimates for interaction logic and research logging.