Safety and Health at Work (Sep 2024)

Management Architecture With Multi-modal Ensemble AI Models for Worker Safety

  • Dongyeop Lee,
  • Daesik Lim,
  • Jongseok Park,
  • Soojeong Woo,
  • Youngho Moon,
  • Aesol Jung

Journal volume & issue
Vol. 15, no. 3
pp. 373 – 378

Abstract

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Introduction: Following the Republic of Korea electric power industry site-specific safety management system, this paper proposes a novel safety autonomous platform (SAP) architecture that can automatically and precisely manage on-site safety through ensemble artificial intelligence (AI) models. The ensemble AI model was generated from video information and worker's biometric information as learning data and the estimation results of this model are based on standard operating procedures of the workplace and safety rules. Methods: The ensemble AI model is designed and implemented by the Hadoop ecosystem with Kafka/NiFi, Spark/Hive, HUE, and ELK (Elasticsearch, Logstash, Kibana). Results: The functional evaluation shows that the main function of this SAP architecture was operated successfully. Discussion: The proposed model is confirmed to work well with safety mobility gateways to provide some safety applications.

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