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This article analyzes the impact of Edge Computing (EC) and Federated Learning (FL) in the context of Industry 5.0, a paradigm that combines advanced technologies with human-machine collaboration to enhance sustainability, personalization, and industrial efficiency. Through a systematic literature review based on the PRISMA framework, key benefits of Edge Computing—such as latency reduction and improved data privacy—were identified, along with the advantages of FL for training distributed models without compromising data security. Finally, A hybrid architecture is proposed that integrates FL with GenAI, serving as a foundation for future research aimed at experimental validation, leveraging the local processing capabilities of Edge Computing and the generative power of AI models to optimize real-time processes. This architecture addresses key challenges of Industry 5.0, including personalization, energy sustainability, and enhanced security in distributed systems.

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Edge Computing and Federated Learning as Enabling Technologies for Industry 5.0: A Literature Review with an Industrial Focus

  • 会议论文

  • 发表日期：

    2026年

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  • Johanna Moreno-Castellanos,
  • Juan M. Núñez Velasco,
  • Fernando De la Prieta

摘要

This article analyzes the impact of Edge Computing (EC) and Federated Learning (FL) in the context of Industry 5.0, a paradigm that combines advanced technologies with human-machine collaboration to enhance sustainability, personalization, and industrial efficiency. Through a systematic literature review based on the PRISMA framework, key benefits of Edge Computing—such as latency reduction and improved data privacy—were identified, along with the advantages of FL for training distributed models without compromising data security. Finally, A hybrid architecture is proposed that integrates FL with GenAI, serving as a foundation for future research aimed at experimental validation, leveraging the local processing capabilities of Edge Computing and the generative power of AI models to optimize real-time processes. This architecture addresses key challenges of Industry 5.0, including personalization, energy sustainability, and enhanced security in distributed systems.