School of Information Technology, Deakin University, Geelong, VIC 3220, Australia.
School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC 3086, Australia.
Sensors (Basel). 2024 Apr 27;24(9):2793. doi: 10.3390/s24092793.
This comprehensive review investigates the transformative potential of sensor-driven digital twin technology in enhancing healthcare delivery within smart environments. We explore the integration of smart environments with sensor technologies, digital health capabilities, and location-based services, focusing on their impacts on healthcare objectives and outcomes. This work analyzes the foundational technologies, encompassing the Internet of Things (IoT), Internet of Medical Things (IoMT), machine learning (ML), and artificial intelligence (AI), that underpin the functionalities within smart environments. We also examine the unique characteristics of smart homes and smart hospitals, highlighting their potential to revolutionize healthcare delivery through remote patient monitoring, telemedicine, and real-time data sharing. The review presents a novel solution framework leveraging sensor-driven digital twins to address both healthcare needs and user requirements. This framework incorporates wearable health devices, AI-driven health analytics, and a proof-of-concept digital twin application. Furthermore, we explore the role of location-based services (LBS) in smart environments, emphasizing their potential to enhance personalized healthcare interventions and emergency response capabilities. By analyzing the technical advancements in sensor technologies and digital twin applications, this review contributes valuable insights to the evolving landscape of smart environments for healthcare. We identify the opportunities and challenges associated with this emerging field and highlight the need for further research to fully realize its potential to improve healthcare delivery and patient well-being.
这篇全面的综述探讨了传感器驱动的数字孪生技术在增强智能环境中的医疗保健服务方面的变革潜力。我们研究了智能环境与传感器技术、数字健康功能和基于位置的服务的集成,重点关注它们对医疗保健目标和结果的影响。这项工作分析了基础技术,包括物联网 (IoT)、医疗物联网 (IoMT)、机器学习 (ML) 和人工智能 (AI),这些技术是智能环境功能的基础。我们还研究了智能家居和智能医院的独特特点,强调它们通过远程患者监测、远程医疗和实时数据共享来彻底改变医疗保健服务的潜力。本综述提出了一个利用传感器驱动的数字孪生体来满足医疗需求和用户需求的新解决方案框架。该框架结合了可穿戴健康设备、人工智能驱动的健康分析和概念验证数字孪生应用程序。此外,我们还探讨了基于位置的服务 (LBS) 在智能环境中的作用,强调其在增强个性化医疗干预和应急响应能力方面的潜力。通过分析传感器技术和数字孪生应用程序的技术进步,本综述为医疗保健的智能环境不断发展的格局提供了有价值的见解。我们确定了与这一新兴领域相关的机遇和挑战,并强调需要进一步研究以充分发挥其提高医疗保健服务和患者福祉的潜力。