使用无线体域网络和物联网的综合医疗监测系统

M. Ezhilarasi, Anand Kumar, M. Shanmugapriya, Anshul Ghanshala, Anshika Gupta
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引用次数: 1

摘要

为了最大限度地降低总体医疗保健成本并增强工作流程和流程,诊所和家庭都需要远程健康监控解决方案。作为最有效的通信技术之一,物联网(IoT)提供了跨各种应用集成数据访问和融合的能力。根据如何定义每个人的角色,用户和合格的专业人员(如医疗行业的医生和护士)可能能够访问数据。医疗行业物联网的目标是通过汇集所有相关部门和尖端技术来重新定义医疗保健系统,从而充分利用使用物联网平台的密切相关技术之间共享的数据。物联网通常被期望提供增强的设备、方案和应用连接,扩展到机器对机器通信。在过去的几年里,可穿戴传感器的发展提供了方便、简单和更好的健康。通过使医疗传感器更小、更便宜,技术进步促进了这些设备的使用。医疗传感器提高了远程健康监测、手术、康复和治疗等医疗保健服务的专业知识和能力。雾计算技术也被加入,以增强精准医疗,获得实时数据处理,并防止连接失败。因此,设备的操作环境更加灵活和本地化。在这方面,本研究提出了一个医疗保健领域的架构模型,该模型结合了身体区域网络、物联网和雾计算技术。关键贡献是通过使用靠近边缘的中间雾层来超越物联网限制,从而提高物联网设备的功能和资源。实验表明,与其他标准体系结构相比,该模型的响应时间提高了75%。评估的结果支持建议的模型在保持应用程序性能的同时实现其目标的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated Healthcare Monitoring System using Wireless Body Area Networks and Internet of Things
To minimize overall healthcare costs and enhance workflows and processes, remote health monitoring solutions are needed in both clinics and at home. One of the most effective communication technologies, the Internet of Things (IoT) offers the ability of integrated data access and fusion across a variety of applications. Depending on how each person's role is defined, users and qualified professionals (like doctors and nurses in the medical industry) may be able to access data. The goal of the Internet of Things in the healthcare industry is to redefine the healthcare system by bringing together all involved authorities and cutting-edge technology makes the most of the data shared between intimately linked technologies that use the IoT platform. IoT is generally anticipated to provide an enhanced device, scheme, and application connectivity that extend over machine-to-machine communications. In the past few years, the development of wearable sensors has offered ease, simplicity, and better health. By making medical sensors smaller and less expensive, technological advancements have boosted the use of these devices. The expertise and abilities of healthcare services, such as remote health monitoring, surgery, rehabilitation, and therapy are improved through medical sensors. Fog computing techniques are also added to enhance precision medicine, obtain real-time data processing, and prevent the connection from failing. As a result, the operating environment for devices is more nimble and local. In this regard, this study suggests an architecture model for the healthcare domain that incorporates the technologies of body area networks, IoT, and Fog computing. The key contribution is to boost the capabilities and resources of IoT devices by using an intermediate Fog layer close to the edge to get beyond IoT restrictions. Experiments show that when compared to other standard architecture, the suggested model can reach a 75% faster response time. The evaluation's results supported the suggested model's ability to accomplish its objectives while maintaining application performance.
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