Framework evaluates hydrogen fuel cell technologies for energy optimization in smart cities, highlighting performance metrics and infrastructure needs.
This study proposes an Artificial Intelligence-Supported Hyperfuzzy framework to evaluate hydrogen fuel cell technologies in Morocco's smart urban and supply chain ecosystems. Integrating compromise-ranking with efficiency benchmarking, the model addresses challenges in performance optimization, decision uncertainty, and supply integration. Key metrics—like power density, fuel efficiency, and system adaptability—are assessed through fuzzy logic and Artificial Intelligence-enhanced sensitivity analysis. Findings confirm that hydrogen-powered public transport offers superior efficiency and robustness, emerging as the top-ranked alternative. Artificial Intelligence strengthens traceability, weight calibration, and adaptability under expert preference variation. The study underscores the importance of supportive infrastructure, including refueling stations and grid-integrated systems, for scalable deployment. Results offer data-driven insights for policymakers and planners, guiding sustainable hydrogen strategies tailored to urban mobility and energy supply networks. By advancing decision accuracy under real-world uncertainty, this framework provides a replicable model for optimizing hydrogen-based solutions in smart cities.
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Tamtam et al. (2025) studied this question.
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