ARGUS / JANUS: Signal Integrity and Adaptive Orchestration
Evidence-led architecture for trustworthy sensing, uncertainty, and bounded machine response
- Programme
- ARGUS / JANUS
- Status
- ARGUS: active signal-integrity and arbitration programme; JANUS: adaptive orchestration architecture in development
- Methods
- Read-only signal validators, evidence fusion, uncertainty-aware arbitration, immutable-source retention, and versioned decision logic
- Objective
- Make signal quality and machine response traceable from source data to downstream action
ARGUS and JANUS occupy two distinct layers of an adaptive systems architecture. ARGUS asks whether an observed structure is trustworthy enough to interpret. JANUS is the adaptive orchestration architecture being developed to decide whether, when, and how downstream components should respond.
Characterise before intervention.
Evidence before action.
ARGUS is an adaptive signal-integrity and arbitration architecture designed to distinguish meaningful structure from artifact before reconstruction, interpretation, or automated response. Its validator suite evaluates complementary evidence across entropy, rhythmic muscle contamination, phase and harmonic structure, coherence, spatiotemporal curvature, transient events, and common-reference behaviour.
Rather than allowing any single threshold to determine the fate of a signal, ARGUS brings these measures into an auditable evidence model capable of preserving, qualifying, attenuating, or deferring—while retaining source integrity, uncertainty, and decision provenance throughout the processing chain.
Immutable source data.
Inspectable evidence from complementary validators.
Uncertainty retained rather than concealed.
Core integrations:
- ARGUS signal-quality evidence and usable-window selection
- Spectral Suite multidimensional signal analysis spanning spectral, temporal, complexity, coherence, coupling, stability, and trajectory dynamics
- TARAN reconstruction or representation learning where validation shows value
Designed for traceability, abstention, and controlled escalation.
ARGUS is progressing towards unified arbitration across raw EEG and derived feature streams, supported by versioned configuration, adaptive event handling, prospective validation, and measured real-time operation. The result will be a configurable fidelity layer that carries signal quality, uncertainty, and traceable decisions into downstream modelling, orchestration, and closed-loop control.
This architecture is relevant wherever noisy, changing data must inform high-consequence decisions—including Defence sensing, neurotechnology, human–AI teaming, and other time-series systems. It supports local/offline operation and auditable handling of uncertainty.
Governance is part of the engineering. Raw data, thresholds, scores, masks, corrections, and decisions should remain versioned and reviewable, with privacy, consent, signal ownership, and safe fallback treated as system requirements.
Collaborate
We welcome research, validation, and integration conversations with organisations developing trustworthy sensing, adaptive decision support, and responsible dual-use systems.
