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<p>Biological laboratories, which are crucial for research and medical trials, often face challenges such as disconnected data, fragmented systems, excessive manual processes, and insufficient smart technology. This study presents a comprehensive intelligent supervision system designed to ensure complete element coverage, full-process supervision, full-chain traceability, and dynamic real-time monitoring within these laboratories. The system incorporates algorithms for personnel behavior identification, secure network transmission, native data storage, aggregation, processing terminals, and intelligent decision-making assistance platforms. Implemented across over 2000 laboratories in Zhejiang Province, the system has identified and mitigated over 20,000 risk points, processed over 3000 early warning instances, and achieved an accuracy rate of exceeding 93% in identifying personnel gestures and behavior. The platform uses cutting-edge technology to address information security and risk classification, supporting comprehensive incident management from pre-incident reviews to closed-loop disposal post-inciden. Additionally, it facilitates tiered management and tracks risk treatment, significantly enhancing the intelligent governance capacity for laboratory safety. Future developments will focus on a people-oriented approach, iterative algorithmic technology, and standardized governance of data substrates.</p>

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Exploration and future prospects of intelligent supervision technology and system development in biological laboratories

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月21日

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  • Yanchao Gao,
  • Hua Gu,
  • Yanfeng Ma

摘要

Biological laboratories, which are crucial for research and medical trials, often face challenges such as disconnected data, fragmented systems, excessive manual processes, and insufficient smart technology. This study presents a comprehensive intelligent supervision system designed to ensure complete element coverage, full-process supervision, full-chain traceability, and dynamic real-time monitoring within these laboratories. The system incorporates algorithms for personnel behavior identification, secure network transmission, native data storage, aggregation, processing terminals, and intelligent decision-making assistance platforms. Implemented across over 2000 laboratories in Zhejiang Province, the system has identified and mitigated over 20,000 risk points, processed over 3000 early warning instances, and achieved an accuracy rate of exceeding 93% in identifying personnel gestures and behavior. The platform uses cutting-edge technology to address information security and risk classification, supporting comprehensive incident management from pre-incident reviews to closed-loop disposal post-inciden. Additionally, it facilitates tiered management and tracks risk treatment, significantly enhancing the intelligent governance capacity for laboratory safety. Future developments will focus on a people-oriented approach, iterative algorithmic technology, and standardized governance of data substrates.