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Risk assessment of biological sample transport by UAVs based on Bayesian networks
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Qing LIU, Tian SHEN
China Safety Science Journal | 2025, 35(1) : 16 - 24
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China Safety Science Journal | 2025, 35(1): 16-24
Safety social science and safety management
Risk assessment of biological sample transport by UAVs based on Bayesian networks
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Qing LIU, Tian SHEN
Affiliations
  • School of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
Published: 2025-01-28 doi: 10.16265/j.cnki.issn1003-3033.2025.01.0441
Outline
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To quantify the transportation risks associated with biological samples using UAVs, this study first identified 32 risk factors across five dimensions-human, machine, environment, management, and hazard-based on national standards and relevant literature. A BN for risk assessment was constructed using Netica software, with prior probabilities determined through expert knowledge and fuzzy set quantitative analysis. The proposed risk assessment model was then used for bidirectional reasoning and scenario analysis. A case study of a UAV company in Shenzhen was presented to evaluate the transportation risks of biological samples and identify key influencing factors. The results indicate that the risk probability of biological sample transportation, as calculated through forward reasoning, is approximately 2.203×10-5. The primary risk factors are related to hazardous materials, followed by equipment and facility-related issues. The core risk factors influencing biological sample transportation include the size, quantity and weight of hazardous material packages, the temperature control effectiveness of specialized cold chain logistics boxes, the integrity of emergency response plans, emergency handling capabilities, safety management and education, and the presence of obstacles.

Bayesian networks (BN)  /  biological samples  /  unmanned aerial vehicle (UAV) transportation  /  risk assessment  /  emergency response
Qing LIU, Tian SHEN. Risk assessment of biological sample transport by UAVs based on Bayesian networks[J]. China Safety Science Journal, 2025 , 35 (1) : 16 -24 . DOI: 10.16265/j.cnki.issn1003-3033.2025.01.0441
Year 2025 volume 35 Issue 1
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2025.01.0441
  • Receive Date:2024-08-07
  • Online Date:2025-07-05
  • Published:2025-01-28
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  • Received:2024-08-07
  • Revised:2024-10-12
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    School of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
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表12种不同金属材料的力学参数

Family
属数
Number of
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种数
Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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