Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress.
Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress.
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DOI：
10.1155/2022/7218113
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发表时间：
2022
影响因子：
--
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中科院分区：
文献类型：
--
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医疗物联网（IoMT）是物联网（IoT）最新兴的时代，因其在智能医疗系统（SHS）中的广泛适用性而日益受到研究人员的关注。由于当前的疫情形势，个人为了一个小问题就去看医生是有很大风险的。因此，使用物联网设备，我们可以轻松监控我们的日常健康记录，从而可以自行采取初步预防措施。 IoMT 在医疗保健行业中发挥着至关重要的作用，以提高电子设备的准确性、可靠性和生产力。这项研究工作概述了物联网，重点关注智能医疗系统 (SHS) 中使用的各种支持技术，例如射频识别 (RFID)、人工智能 (AI) 和区块链。我们对几位研究人员提出的各种 IoMT 架构进行了比较分析。此外，我们还定义了物联网的各个健康领域，包括分析不同传感器的应用环境、优缺点。此外，我们还找出了基于 IoMT 网络的智能医疗系统实施过程中需要考虑的关键协议设计挑战。考虑到这些挑战，我们准备了一项针对不同数据收集技术的比较研究，这些技术可用于保持收集数据的准确性。此外，这项研究工作还提供了基于各种参数（例如能耗、数据包传输率、电池寿命、服务质量、功耗、网络吞吐量、延迟和传输速率）维持基于人工智能的 IoMT 框架的能源效率的全面研究。最后，我们提供了不同的相关方程，用于使用人工智能找到基于 IoMT 的医疗保健系统的准确性和效率。我们根据不同的数据收集算法的准确性和错误率以图形方式对其进行了比较。同样，不同的能效算法也根据其能耗和丢包百分比进行了图形化比较。我们分析了本研究中使用的参考文献，并根据其出版年份和出版途径的分布以图形方式表示。
Internet of Medical Thing (IoMT) is the most emerging era of the Internet of Thing (IoT), which is exponentially gaining researchers' attention with every passing day because of its wide applicability in Smart Healthcare systems (SHS). Because of the current pandemic situation, it is highly risky for an individual to visit the doctor for every small problem. Hence, using IoMT devices, we can easily monitor our day-to-day health records, and thereby initial precautions can be taken on our own. IoMT is playing a crucial role within the healthcare industry to increase the accuracy, reliability, and productivity of electronic devices. This research work provides an overview of IoMT with emphasis on various enabling techniques used in smart healthcare systems (SHS), such as radio frequency identification (RFID), artificial intelligence (AI), and blockchain. We are providing a comparative analysis of various IoMT architectures proposed by several researchers. Also, we have defined various health domains of IoMT, including the analysis of different sensors with their application environment, merits, and demerits. In addition, we have figured out key protocol design challenges, which are to be considered during the implementation of an IoMT network-based smart healthcare system. Considering these challenges, we prepared a comparative study for different data collection techniques that can be used to maintain the accuracy of collected data. In addition, this research work also provides a comprehensive study for maintaining the energy efficiency of an AI-based IoMT framework based on various parameters, such as the amount of energy consumed, packet delivery ratio, battery lifetime, quality of service, power drain, network throughput, delay, and transmission rate. Finally, we have provided different correlation equations for finding the accuracy and efficiency within the IoMT-based healthcare system using artificial intelligence. We have compared different data collection algorithms graphically based on their accuracy and error rate. Similarly, different energy efficiency algorithms are also graphically compared based on their energy consumption and packet loss percentage. We have analyzed our references used in this study, which are graphically represented based on their distribution of publication year and publication avenue.
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影响因子：
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作者：
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DOI：
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发表时间：
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影响因子：
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影响因子：
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