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Human-Centered Edge AI and Wearable Technology for Workplace Health and Safety in Industry 5.0

In: Artificial Intelligence for Safety and Reliability Engineering

Author

Listed:
  • Tho Nguyen

    (Dong A University)

  • Dac Hieu Nguyen

    (Dong A University
    Thuyloi University)

  • Quoc-Thông Nguyen

    (Dong A University)

  • Kim Duc Tran

    (Dong A University)

  • Kim Phuc Tran

    (Dong A University
    ULR 2461 - GEMTEX - Génie et Matériaux Textiles)

Abstract

This research explores the integration of human-centered edge artificial intelligence (AI) and wearable technology to enhance workplace health and safety within Industry 5.0. It highlights the importance of real-time monitoring and analysis facilitated by wearable devices equipped with sensors to measure physiological and environmental parameters, which help prevent hazards and accidents. Leveraging the Industrial Internet of Things (IIoT), these wearable technologies continuously track worker health and environmental conditions, promoting proactive hazard prevention and improving workplace efficiency. The role of edge AI is emphasized for its ability to enable immediate decision-making and reduce latency by processing data closer to its source, thereby enhancing worker safety and productivity while addressing ethical concerns related to privacy and security. The potential of human-centered edge AI and wearable technology to foster a collaborative and sustainable industrial environment is significant, though challenges such as limited computational resources and battery life constraints require ongoing research and development. This comprehensive analysis underscores the transformative impact of these technologies on workplace health and safety and the necessity for innovative solutions to overcome current limitations, aiming to improve worker well-being and boost industrial efficiency and productivity.

Suggested Citation

  • Tho Nguyen & Dac Hieu Nguyen & Quoc-Thông Nguyen & Kim Duc Tran & Kim Phuc Tran, 2024. "Human-Centered Edge AI and Wearable Technology for Workplace Health and Safety in Industry 5.0," Springer Series in Reliability Engineering, in: Kim Phuc Tran (ed.), Artificial Intelligence for Safety and Reliability Engineering, pages 171-183, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-71495-5_8
    DOI: 10.1007/978-3-031-71495-5_8
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