PRRS: A Distributed Passive Resonance Sensing Framework for Large-Scale Disaster Detection

PRRS — Passive Resonance Relay System: Technical ReviewPRRS approaches environmental sensing as a problem of extracting structure from RF fields that already exist in the environment, rather than actively interrogating a target. Most conventional sensing systems assume some degree of cooperation, dedicated illumination, or clear signal dominance over background. PRRS instead assumes the opposite starting condition: the RF environment is already saturated with ambient signals — broadcast, telecom, and other incidental sources — and treats detection as the task of identifying persistent deviations within that existing field, rather than generating and interpreting a dedicated return signal.Concretely, this means monitoring passive resonance signatures from distributed relay nodes for statistically persistent shifts in backscatter characteristics — amplitude, phase, or harmonic content — that correlate with a physical disturbance (ground displacement, structural movement, water intrusion) rather than transient noise. A single anomalous reading is not treated as a detection; only a deviation that persists across multiple observation windows is escalated, which is the "trading resolution for continuity" trade-off: individual nodes are low-precision and inexpensive, but the network compensates through redundancy and temporal persistence rather than per-node accuracy.This gives the system two practical properties relevant to disaster-response deployment: it requires no dedicated illumination infrastructure (it rides on ambient RF rather than needing its own transmitter network), and it degrades gracefully — losing individual nodes to damage or debris burial reduces spatial resolution incrementally rather than causing total system failure, which matters for the infrastructure-degraded conditions (post-landslide, post-flood) this system targets.This document covers system architecture, signal interaction principles, and deployment logic for environmental and disaster monitoring — landslide, flood, and structural-collapse detection in zero- or degraded-infrastructure settings.