Industry 4.0 Driven Risk Management for Climate Resilient Smart Cities A Hybrid Framework for Southeastern Türkiye

This study presents a Hybrid Digital-Physical Risk Management Framework designed to enhance urban climate resilience through the integration of Industry 4.0 technologies. By combining real-time IoT sensor networks, AI-based predictive analytics, and blockchain-secured governance, the framework enables anticipatory risk detection, infrastructure adaptation, and decentralized disaster coordination. Applied to four climate-vulnerable cities in Türkiye Gaziantep, Mardin, Diyarbakır, and Adana the model demonstrated a 20% improvement in risk prediction accuracy, a 67% reduction in emergency response time, and a 35% increase in infrastructure resilience. AI models, including LSTM and CNN, were used for time-series forecasting and hazard classification, while digital twins simulated disaster impacts on urban systems. Results underscore the feasibility of deploying cyber-physical systems in mid-sized cities, despite challenges related to sensor coverage, data interoperability, and regulatory fragmentation. The framework offers a scalable, transferable solution for climate-adaptive urban governance, with significant implications for policy, infrastructure planning, and smart city transformation. Findings support broader application across other at-risk regions and highlight the need for ethical AI deployment, data transparency, and regulatory support. This work contributes a replicable model for future-ready cities seeking to operationalize digital intelligence for climate risk mitigation.