Goffari Madthing@Fanizu

In Thailand, a 191 emergency call travels through three relays — the provincial center answers, phones the district station, which then radios the patrol officer covering the area. Every relay costs minutes, real phone lines carry no GPS, and panicked callers describe locations in local slang no map understands. Emergency Smart Dispatcher cuts all of that down to one click. When a caller speaks, Whisper transcribes Thai speech in near real time while DeepSeek V4 (via Fireworks AI) triages the incident as they talk: type, urgency 1–5, sentiment, and recommended units, following a rubric we defined. Location is resolved in three layers — device GPS when available, a RAG landmark base that matches colloquial and even mispronounced place names by sound rather than spelling, and a geocoding ladder that trims filler words until the map finds the spot. The system then identifies the exact duty officer for that patrol zone and, with one click, sends the full picture to the officer's screen: urgency, live transcript, incident map, and turn-by-turn navigation. The officer acknowledges and reports back; the dispatcher can answer the call over WebRTC and send human-verified notes — AI proposes, a human finalizes. Every layer has a fallback: we validated Whisper large-v3 on an AMD Instinct MI300X (ROCm), and if the cloud drops mid-call the system switches to the local model baked into our single Docker image. Officer rosters are transparent demo data; production integrates real duty rosters. Built by team emergency-smart-dispatcher for AMD Developer Hackathon: ACT II.

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