2025 Vol.8 Dec.N06

• Title: Design and Application of a Cloud-Based Intelligent Remote Teaching System for Medical Nursing
• Name: Cuifan Li , Yingdong Cao*, Pengfei Ren , Qin Bai ,Huan Li
• Company: Sias University School of Medicine，Xinzheng 451100 China
• Abstract:

   Medical nursing teaching systems predominantly rely on traditional models, typically conducted in fixed locations with teaching resources stored on local servers. Knowledge transfer follows fixed schedules and standardized teaching methods. Neglecting the quantifiable differences in teaching resources results in suboptimal recommendation effectiveness. To address this, this paper proposes the design and application of a cloud-based remote intelligent teaching system for medical nursing. It employs a dual-core processor and a storage solution combining solid-state drives (SSDs) with mechanical hard drives (HDDs). Edge computing nodes are centered around embedded processors with a 2.5GHz clock speed and equipped with multiple sensor interfaces. Medical nursing teaching resources undergo fuzzy processing, categorizing them into quantifiable and non-quantifiable resources, processed using equal-average percentage and trapezoidal fuzzy methods respectively. Resources are distributed using a consistent hashing mechanism and dynamically migrated based on storage utilization and access frequency. Exponential smoothing is employed for load forecasting, while big data analytics enables intelligent resource classification, recommendation, and personalized customization. Experimental validation of the proposed method's recommendation accuracy demonstrated that during simulated remote teaching scenarios, the system achieved a resource-learning objective match rate exceeding 0.75, indicating highly satisfactory recommendation performance.

  
  

• Keyword: Cloud Computing; Medical Nursing; Smart Teaching; System Design; Resource Recommendation
• DOI: 10.12250/jpciams2025091106
• Citation form: Cuifan Li , Yingdong Cao*, Pengfei Ren , Qin Bai ,Huan Li .Design and Application of a Cloud-Based Intelligent Remote Teaching System for Medical Nursing[J]. Computer Informatization and Mechanical System,2025,Vol.8,pp.

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