Abstract :

The rapid urbanization and growing complexity of cities demand innovative approaches to resource management and sustainability. This study introduces an adaptive ecosystem model for intelligent urban systems, integrating Industry 5.0 principles to enhance energy and resource management. The proposed framework combines multi-agent systems, predictive analytics, and real-time optimization to address challenges in energy allocation, environmental impact, and urban resilience. The mathematical model incorporates cost and emission constraints, ensuring an optimal balance between economic and environmental objectives.

Simulation results demonstrate significant improvements in energy efficiency and reductions in carbon emissions, validating the model’s applicability across various urban scenarios. The study highlights the integration of IoT, AI, and big data as pivotal components in advancing the operational and decision-making capabilities of smart cities. This research contributes to bridging the gap between technology-driven solutions and human-centric urban planning, offering practical insights for policymakers and urban developers to foster sustainable growth in intelligent cities.

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Keywords :

Adaptive ecosystems, Energy optimization, Industry 5.0, Intelligent urban systems, Sustainable resource management.

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