[Global Livingry Governance Architecture | Part 12]: Autonomous Tsunami Early Warning and Emergency Response System Architecture: Integration of Community Camera Networks, Subsea Station UAVs, Security Systems, Edge AI, and Tensor Stress Index (TSI_{t+1})

Abstract

Disaster management and mitigation in coastal regions and tectonic fault zones require a fundamental shift from manual, expert-committee-dependent response models to closed-loop automated architectures. By combining the Tensor Stress Index function (TSI_{t+1}), Edge AI processing, distributed community observation networks, security systems, and reconnaissance drones (UAVs) deployed from subsea stations, the system establishes a high-speed defense layer that optimizes both cost-efficiency and operational reliability. This paper presents an integrated system architecture featuring: The TSI_{t+1} Function: A multidimensional variable space that aggregates tectonic displacement velocity, subsea pressure, coastal water level, microseisms, and shelf tilt, modulated by spatial risk multipliers (R_{risk}) to automatically trigger emergency states. Micro-Sandbox Field Tier: Flexible utilization of fixed community cameras, civilian devices, and subsea station UAVs to establish continuous 24/7 baseline observation and targeted high-resolution reconnaissance. Closed-Loop Automated Response: Automated anomaly detection, low-latency live video verification, tactical navigation, and federated learning integration for continuous accuracy refinement. LERC Financial Framework Integration: Linking verified edge data and smart contracts with Local Ecological Recovery Credit (LERC) mechanisms for transparent, automated emergency resource and capital disbursement without bureaucratic delays. Through comprehensive operational scenarios and parameter evolution models, this architecture demonstrates a paradigm shift toward real-time, autonomous, and financially sustainable coastal disaster governance.