Estimation of Kinetic Energy Harvesting Potential for Self-Powered Wearable IoT Devices With 67 000 Participants From the UK Biobank
Estimation of Kinetic Energy Harvesting Potential for Self-Powered Wearable IoT Devices With 67 000 Participants From the UK Biobank
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DOI：
10.1109/jiot.2023.3288212
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发表时间：
2021-06
影响因子：
10.6
通讯作者：
Christopher Beach;A. Casson
中科院分区：
文献类型：
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作者：
Christopher Beach;A. Casson
从人体运动中收集能量可以减少可穿戴物联网（IoT）设备对电池充电的依赖。然而，迄今为止，估计能量收集潜力的研究主要集中在实验室环境中的小规模健康人群，而不是具有人口水平参与者数量的自由生活环境。在这里，我们通过利用从英国生物银行收集的67,000多名参与者的活动数据，对能量收集潜力进行了有史以来最大的调查。本文详细介绍了一周中的哪一天和参与者的年龄如何影响能量收集潜力，以及疾病（如糖尿病）的存在如何影响预期的能量收集器输出。我们使用动能收集器模型处理加速度计数据，以研究高时间分辨率的功率输出。我们的结果确定了一天中有电力可用的时间之间的关键差异，以及电力输出与参与者年龄之间的反比关系。我们还发现，糖尿病的存在大大降低了能量收集产出，减少了21%以上。研究结果突出了物联网和可穿戴能量收集的一个关键挑战：可穿戴设备旨在监测健康状况，能量收集旨在使设备更加自主，但医疗条件的存在可能会导致能量收集潜力大大降低。研究结果表明，当能源自主成为目标时，满足监测疾病所需的电力预算是多么具有挑战性。
Energy harvesting from human motion can reduce reliance on battery recharging in wearable Internet of Things (IoT) devices. However, to date, studies estimating energy harvesting potential have largely focused on small scale, healthy, population groups in laboratory settings rather than free-living environments with population level participant numbers. Here, we present the largest ever investigation into energy harvesting potential by utilizing the activity data collected in the UK Biobank from over 67000 participants. This article presents detailed stratification into how the day of the week and participant age affect harvesting potential, as well as how the presence of conditions (such as diabetes, which we investigate here) may affect the expected energy harvester output. We process accelerometery data using a kinetic energy harvester model to investigate power output at a high temporal resolution. Our results identify key differences between the times of day when the power is available and an inverse relationship between power output and participant age. We also identify that the presence of diabetes substantially reduces energy harvesting output, by over 21%. The results presented highlight a key challenge in IoT and wearable energy harvesting: that wearable devices aim to monitor health and wellness, and energy harvesting aims to make devices more energy autonomous, but the presence of medical conditions may lead to substantially lower energy harvesting potential. The findings indicate how it is challenging to meet the required power budget to monitor diseases when energy autonomy is a goal.