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<p>This research presents an innovative smart community interactive art therapy platform that integrates multimodal computer graphics with resilient artificial intelligence adaptation mechanisms to address the growing challenges of home-based elderly care. The platform employs a four-layered hierarchical architecture encompassing perception, network, platform, and application layers to deliver personalized therapeutic interventions. The system utilizes multimodal data fusion algorithms to process visual, auditory, and haptic inputs while implementing adaptive learning mechanisms that continuously optimize user experiences based on individual preferences and capabilities. Experimental validation demonstrates superior performance with response times averaging 387 ms under 100 concurrent users, therapeutic recommendation accuracy of 87.3%, and user satisfaction scores of 4.2/5.0 across multiple evaluation dimensions. The resilient adaptation mechanisms achieved 99.7% service availability and 34% improvement in CPU utilization compared to conventional systems. Long-term usage tracking revealed sustained engagement patterns with minimal dropout rates over 6-month evaluation periods. The platform successfully addresses key limitations of traditional elderly care models by providing comprehensive support that encompasses cognitive stimulation, emotional well-being, and social connection while maintaining cost-effectiveness and scalability for large-scale deployment in smart community environments.</p>

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A smart community interactive art therapy platform based on multimodal computer graphics and resilient artificial intelligence for home-based elderly care

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月3日

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  • DianDian Sang,
  • Ling Miao,
  • Qitao Wu

摘要

This research presents an innovative smart community interactive art therapy platform that integrates multimodal computer graphics with resilient artificial intelligence adaptation mechanisms to address the growing challenges of home-based elderly care. The platform employs a four-layered hierarchical architecture encompassing perception, network, platform, and application layers to deliver personalized therapeutic interventions. The system utilizes multimodal data fusion algorithms to process visual, auditory, and haptic inputs while implementing adaptive learning mechanisms that continuously optimize user experiences based on individual preferences and capabilities. Experimental validation demonstrates superior performance with response times averaging 387 ms under 100 concurrent users, therapeutic recommendation accuracy of 87.3%, and user satisfaction scores of 4.2/5.0 across multiple evaluation dimensions. The resilient adaptation mechanisms achieved 99.7% service availability and 34% improvement in CPU utilization compared to conventional systems. Long-term usage tracking revealed sustained engagement patterns with minimal dropout rates over 6-month evaluation periods. The platform successfully addresses key limitations of traditional elderly care models by providing comprehensive support that encompasses cognitive stimulation, emotional well-being, and social connection while maintaining cost-effectiveness and scalability for large-scale deployment in smart community environments.