RelayZero: Offline Edge-AI Semantic Compression for Disaster Mesh Networks

Описание и применение

RelayZero снижает размер сообщений о чрезвычайных ситуациях до 25 байт, обеспечивая надёжную передачу через низкоскоростные радиосети.

Задача

Centralized telecoms fail during disasters, leaving rescue teams with low‑bandwidth sub‑GHz mesh radios that choke on standard voice or text traffic.

Результат

RelayZero enables reliable, low‑bandwidth emergency communication by compressing dispatches into a 25‑byte packet, achieving ~88% data reduction and allowing critical alerts to traverse fragile mesh radios.

Рабочий процесс

• 1. Responder speaks or types dispatch into Python UI (transmitter.py).
• 2. Local Gemma 4:E2B model (via Ollama) parses input, extracts Priority, Location, Hazard, Casualties, Requirements, and serializes into 25‑byte string.
• 3. Packet sent over local TCP socket (simulating LoRa UART).
• 4. Base station (base_station.py) receives packet on port 5000, maps coordinates on offline OpenStreetMap, draws 150‑m danger perimeter.
• 5. If packet flagged CRITICAL, frontend synthesizes 2‑second police siren using Web Audio API.
• 6. Triage officers export queue to CSV for post‑operation forensics.

Доказательства

RelayZero is a 100% offline, edge‑AI semantic compression protocol.

Источник

It uses Gemma 4 : E2B to strip away conversational filler, extract the vital triage facts, and compress the dispatch into a dense 25‑byte telemetry packet formatted as: PRIO:CRITICAL | LOC:LIBRARY | HAZ:FIRE | CAS:2 | REQ:MEDICS

Источник

This intelligent edge compression yields an ~88% reduction in data size, allowing life‑saving SOS alerts to slip effortlessly through low‑power mesh radios.

Источник