T. Frissore
Balboa A.L.S., Florida, United States
Keywords: RF sensing, acoustic detection, edge AI, mesh networking, C-UAS
WavWhispr is a modular edge sensing platform designed to autonomously detect and classify RF emissions in real time, enabling situational awareness and threat alerting in EM-contested environments. Each unit integrates a software-defined radio (SDR), embedded AI processor, and secure mesh communications to enable persistent surveillance without requiring access to traditional communications infrastructure. The system captures raw RF data, extracts signal features, and uses trained models to classify known threats (e.g., drone uplinks, spoofed comms, unauthorized transmissions), while flagging anomalies for operator review. Each node is capable of standalone operation, but when deployed in a network, WavWhispr nodes automatically form a secure mesh that allows them to share threat signals, reinforce confidence levels, and relay alerts across extended terrain. Alerts can be triggered even in GPS- and bandwidth-denied environments, with real-time relays to tactical operators or central command nodes. Built with open software architecture and COTS hardware, WavWhispr supports plug-and-play upgrades for future sensing modalities such as acoustic detection or GNSS spoofing recognition. Firmware and AI models can be updated over the air, allowing rapid adaptation to evolving threat profiles or region-specific mission needs.