Saf Health Work.  2024 Sep;15(3):373-378. 10.1016/j.shaw.2024.04.008.

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

• Lee D
• Lim D
• Park J
• Woo S
• Moon Y
• Jung A

• KMID: 2559876
• DOI: http://doi.org/10.1016/j.shaw.2024.04.008

Abstract

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.

Keyword

Autonomous platform; Ensemble AI; Power industry; Risk index; Safety management