Emerging indoor photovoltaics for self-powered and self-aware IoT towards sustainable energy management.
Emerging indoor photovoltaics for self-powered and self-aware IoT towards sustainable energy management.
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DOI：
10.1039/d3sc00659j
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发表时间：
2023-05-24
期刊：
影响因子：
8.4
通讯作者：
中科院分区：
文献类型：
--
作者：
随着物联网设备的数量迅速增加，迫切需要周围环境中的可持续和高效的能源和管理实践。作为回应，我们开发了一种基于可持续无毒材料的高效环境光伏，并在仅由环境光采集器供电的物联网传感器上使用设备上预测，全面实现了基于长短期记忆（LSTM）的能源管理。电力由基于铜（ii/i）电解质的染料敏化光伏电池提供，其具有前所未有的38%的电力转换效率和1000勒克斯（荧光灯）下的1.0 V开路电压。设备上的LSTM预测不断变化的部署环境，并相应地调整设备的计算负载，以永久运行能量收集电路，避免功率损耗或停电。将环境光采集与人工智能相结合，可以开发出完全自主、自供电的传感器设备，这些设备可用于各行各业、医疗保健、家庭环境和智能城市。由铜电解质基染料敏化光伏电池作为环境光收集器供电的物联网设备实现了38%的功率转换效率，并集成了动态智能设备能源管理系统。
As the number of Internet of Things devices is rapidly increasing, there is an urgent need for sustainable and efficient energy sources and management practices in ambient environments. In response, we developed a high-efficiency ambient photovoltaic based on sustainable non-toxic materials and present a full implementation of a long short-term memory (LSTM) based energy management using on-device prediction on IoT sensors solely powered by ambient light harvesters. The power is supplied by dye-sensitised photovoltaic cells based on a copper(ii/i) electrolyte with an unprecedented power conversion efficiency at 38% and 1.0 V open-circuit voltage at 1000 lux (fluorescent lamp). The on-device LSTM predicts changing deployment environments and adapts the devices' computational load accordingly to perpetually operate the energy-harvesting circuit and avoid power losses or brownouts. Merging ambient light harvesting with artificial intelligence presents the possibility of developing fully autonomous, self-powered sensor devices that can be utilized across industries, health care, home environments, and smart cities. IoT devices powered by copper electrolyte-based dye-sensitized photovoltaic cells as ambient light harvesters achieve 38% power conversion efficiency and incorporate a dynamic intelligent on-device energy management system.
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影响因子：
1.6
作者：
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通讯作者：
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影响因子：
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影响因子：
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作者：
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影响因子：
7.9
作者：
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DOI：
10.1016/j.future.2013.01.010
发表时间：
2013-09-01
影响因子：
7.5
作者：
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通讯作者：
Palaniswami, Marimuthu