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Design of an energy-efficient IoT device with optimized data management in sports person health monitoring application
Transactions on Emerging Telecommunications Technologies ( IF 2.5 ) Pub Date : 2021-04-17 , DOI: 10.1002/ett.4258 Yonghong Qiu 1 , Gaicheng Liu 1 , Bala Anand Muthu 2 , C. B. Sivaparthipan 3
Transactions on Emerging Telecommunications Technologies ( IF 2.5 ) Pub Date : 2021-04-17 , DOI: 10.1002/ett.4258 Yonghong Qiu 1 , Gaicheng Liu 1 , Bala Anand Muthu 2 , C. B. Sivaparthipan 3
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The improvements in health habits, technological advances, and the proliferation of healthy living activities have contributed to the comprehensive extension of sports person health assessment. Since the internet of things (IoT) device requires energy-optimized wearable devices, it has been observed that the demanding factors include energy efficiency factor in Sports Person Health Monitoring wearable device. Hence in this paper, IoT-based Hierarchical Health Monitoring Model (IoT-HHMM) is proposed to improve the efficiency factor by minimizing the energy consumption to achieve effective assessment of sports person health monitoring wearables. The complexity of limited resources and usage of energy is optimized by introducing the Optimal Energy-Efficient Resource Assignment Algorithm. Likewise, a cloud computing technique is implemented using Probabilistic Radial Basis Function Neural Network to ensure effective prediction and classification in healthcare data management, which is considered as a significant factor in wearable IoT devices for Sports Person Health Monitoring. The result indicates that the proposed IoT-HHMM achieves a high accuracy ratio of 98.4%, a sensitivity ratio of 92.5%, a performance ratio of 96.7% when compared to traditional approaches.
中文翻译：
在运动者健康监测应用中优化数据管理的节能物联网设备设计
健康习惯的改善、技术的进步、健康生活活动的普及，促进了运动者健康评估的全面延伸。由于物联网 (IoT) 设备需要能量优化的可穿戴设备，据观察，要求的因素包括运动人员健康监测可穿戴设备中的能效因素。因此，本文提出了基于物联网的分层健康监测模型（IoT-HHMM），通过最小化能耗来提高效率因子，从而实现对运动人士健康监测可穿戴设备的有效评估。通过引入最优能效资源分配算法，优化了有限资源的复杂性和能源的使用。同样地，使用概率径向基函数神经网络实施云计算技术，以确保医疗数据管理中的有效预测和分类，这被认为是可穿戴物联网设备中用于运动人员健康监测的重要因素。结果表明，与传统方法相比，所提出的IoT-HHMM实现了98.4%的高精度、92.5%的灵敏度和96.7%的性能比。
更新日期：2021-04-17
中文翻译：
在运动者健康监测应用中优化数据管理的节能物联网设备设计
健康习惯的改善、技术的进步、健康生活活动的普及，促进了运动者健康评估的全面延伸。由于物联网 (IoT) 设备需要能量优化的可穿戴设备，据观察，要求的因素包括运动人员健康监测可穿戴设备中的能效因素。因此，本文提出了基于物联网的分层健康监测模型（IoT-HHMM），通过最小化能耗来提高效率因子，从而实现对运动人士健康监测可穿戴设备的有效评估。通过引入最优能效资源分配算法，优化了有限资源的复杂性和能源的使用。同样地，使用概率径向基函数神经网络实施云计算技术，以确保医疗数据管理中的有效预测和分类，这被认为是可穿戴物联网设备中用于运动人员健康监测的重要因素。结果表明，与传统方法相比，所提出的IoT-HHMM实现了98.4%的高精度、92.5%的灵敏度和96.7%的性能比。
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