Research on the Framework Design of an AI-IoT Integrated Evaluation Large Language Model Focused on Children's Health and Disease Prevention at High Altitude

Children living in high-altitude plateau regions face unique health challenges due to chronic hypoxia, limited medical resources, and complex environmental factors. Traditional pediatric healthcare approaches often fall short in providing precise, timely, and personalized care in these areas. To address these limitations, this paper proposes an intelligent health assessment and disease early-warning framework tailored for plateau children. The system integrates large language models (LLMs) and Internet of Things (IoT) technologies to support multimodal data collection and real-time remote monitoring. By combining wearable sensor data, clinical records, medical imaging, and genetic information, the framework enables cloud-based analysis, intelligent reasoning, and individualized feedback. We detail the system architecture, core components, and data processing flow, and further explore the potential of AI-IoT fusion in transforming pediatric health management in under-resourced, high-altitude environments.