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Explainable Artificial Intelligence (XAI) plays a crucial role in making AI-driven technologies in smart cities more transparent and understandable. As smart cities integrate AI to improve services like traffic management, energy distribution, and healthcare, the need for trust and accountability becomes more prominent. XAI explains AI decisions in a way that allows all stakeholders, from policymakers to citizens, to understand the reasoning behind critical AI-driven actions. This chapter discusses several architectural models that can be adopted for embedding XAI within smart city operation frameworks, namely centralized, decentralized, and layered systems. Real-world examples, like Barcelona’s AI-powered traffic management system, demonstrate the practical application of XAI in enhancing urban efficiency while maintaining transparency.

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Explainable AI for Future Smart Cities: Architectures, Applications, and Challenges

  • 章节

  • 发表日期：

    2026年

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  • Sara Khader,
  • Qasem Abu Al-Haija

摘要

Explainable Artificial Intelligence (XAI) plays a crucial role in making AI-driven technologies in smart cities more transparent and understandable. As smart cities integrate AI to improve services like traffic management, energy distribution, and healthcare, the need for trust and accountability becomes more prominent. XAI explains AI decisions in a way that allows all stakeholders, from policymakers to citizens, to understand the reasoning behind critical AI-driven actions. This chapter discusses several architectural models that can be adopted for embedding XAI within smart city operation frameworks, namely centralized, decentralized, and layered systems. Real-world examples, like Barcelona’s AI-powered traffic management system, demonstrate the practical application of XAI in enhancing urban efficiency while maintaining transparency.