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DATO: Decentralized Autonomous Traffic Orchestration The Problem: Modern smart-city traffic systems rely entirely on cloud connectivity. If the internet goes down, intersections revert to stupid timers, causing gridlock and endangering emergency vehicles. The Solution: DATO is an asymmetric Cloud-to-Edge AI system designed for 100% offline-resilient traffic management. Instead of building a basic LLM chatbot, I engineered a true multi-agent architecture: The Cloud Teacher (Strategic Agent): Powered by Gemini 3.5 Flash using the new Function Calling SDK. An operator can type natural language emergency commands (e.g., "Clear path for ambulance on North road"). Gemini autonomously calls tools to read the physical intersection sensors, formulates a strategy, and pushes a JSON macro-directive. The Edge Student (Tactical Agent): A localized Gemma 4 model running directly at the intersection. It reads the Cloud's directive and implements a continuous Sense -> Decide -> Act -> Check loop. Why it matters: Because heavy strategic reasoning happens in the cloud and tactical execution happens at the edge, the system is completely offline resilient. If the Wi-Fi is cut, the Gemma 4 Edge Node continues running the intersection safely and autonomously using local heuristic fallback loops and the last known directive.

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