Flora Voice: An Autonomous Cyber-Physical Phyto-Telemetry Node for Early Wildfire Radiant Heat and Mechanical Intrusion Detection via Vascular Biopotential Signal Processing

Early detection of wildfires and perimeter wildlife intrusions in agricultural and forestry borderlands remains a critical challenge due to the line-of-sight limitations and prohibitive costs of conventional optical camera networks and dense wireless sensor grids. This paper presents Flora Voice, a low-cost ($15–20 USD), autonomous cyber-physical phyto-telemetry node that transforms living perimeter trees into biological early-warning sensors by continuously monitoring vascular (xylem/phloem) biopotential signals. Utilizing stainless-steel sub-dermal probes shielded via a grounded Faraday coaxial architecture, microvolt-level physiological signals—specifically fast Action Potentials (AP) and slow Variation Potentials (VP)—are digitized through a 16-bit sigma-delta ADC (TI ADS1115) and processed on an ESP32 microcontroller. We formulate the underlying electrochemical dynamics using the Goldman-Hodgkin-Katz (GHK) membrane equation coupled with inhomogeneous phloem cable theory and Stefan-Boltzmann radiant heat transfer models. An autonomous 10-second dynamic baseline calibration routine compensates for inter-species impedance variance, while a C++ Dual-Layer Stress Analysis algorithm decouples high-slew-rate mechanical trauma (wildlife/human contact) from sustained radiant thermal depolarization preceding flame contact. Both in-silico numerical simulations and in-vivo experimental trials on Persea americana saplings confirm that Flora Voice reliably detects pre-ignition radiant heat waves seconds before leaf combustion and instantaneously flags mechanical impacts, synthesizing zero-latency local acoustic alerts via native I2S hardware drivers without cloud dependency.