隨著科技迅速發展，越來越多的醫療體系開始使用數位醫療並搭配各種感測裝置來協助病患進行治療與復健。透過感測裝置蒐集數據，提供數據分析、健康監控和反饋。同時，少子化和人口老化問題日益加劇，導致醫療需求迅速增長，對現有的醫療系統造成巨大壓力。傳統醫療系統在面對醫療資源分配不均、人力資源短缺和醫療成本增加等挑戰時顯得越來越困難。尤其是不同病症所需的感測裝置各異，導致裝置管理和數據整合上的困難更加突出。 本論文研究開發了一個智慧醫療物聯網平台，整合物聯網技術，以實現對醫療裝置的高效管理和應用。該平台能夠即時監控和管理各種醫療設備，透過收集和分析來自多種感測設備（如VR頭盔和腦波感應器）的數據，提供準確的患者生理狀況資訊。平台利用物聯網技術，實現數據的即時傳輸和處理，並透過AI分析模組進行深度學習和預測分析，最後生成可視化報表供醫療人員參考和診斷，從而提升醫療服務效率，優化醫療資源配置。;With the rapid advancement of technology, an increasing number of healthcare systems are adopting digital healthcare and various sensing devices to assist patients in their treatment and rehabilitation. These sensing devices collect data, providing data analysis, health monitoring, and feedback. Simultaneously, the issues of declining birthrates and an aging population are exacerbating, leading to a substantial increase in healthcare demand, thereby putting immense pressure on existing healthcare systems. Traditional healthcare systems are struggling to cope with challenges such as uneven distribution of medical resources, workforce shortages, and rising medical costs. The diverse requirements of different medical conditions for specific sensing devices further complicate device management and data integration. This thesis develops an intelligent healthcare IoT platform that integrates IoT technology to achieve efficient management and application of medical devices. The platform can monitor and manage various medical devices in real-time, collecting and analyzing data from multiple sensing devices (such as VR headsets and EEG sensors) to provide accurate patient physiological information. Utilizing IoT technology, the platform enables instant data transmission and processing, and through AI analysis modules, it performs deep learning and predictive analysis, generating visual reports for medical personnel reference and diagnosis. This enhances healthcare service efficiency and optimizes the allocation of medical resources.
