research-article

Energy management algorithm for solar‐powered energy harvesting wireless sensor node for Internet of Things

Authors:

Minchul Shin,

Inwhee JoeAuthors Info & Claims

IET Communications, Volume 10, Issue 12

Pages 1508 - 1521

https://doi.org/10.1049/iet-com.2015.0223

Published: 01 August 2016 Publication History

Abstract

The solar powered energy harvesting sensor node is a key technology for Internet of Things (IoT), but currently it offers only a small amount of energy storage and is capable of harvesting only a trivial amount of energy. Therefore, new technology for managing the energy associated with this sensor node is required. In particular, it is important to manage the transmission interval because the level of energy consumption during data transmission is the highest in the sensor node. If the proper transmission interval is calculated, the sensor node can be used semi‐permanently. In this study, the authors propose an energy prediction algorithm that uses the light intensity of fluorescent lamps in an indoor environment. The proposed algorithm can be used to accurately estimate the amount of energy that will be harvested by a solar panel using a weighted average for light intensity. Then, the optimal transmission interval is calculated using the amount of predicted harvested energy and residual energy. The results from the authors’ experimental testbeds show that their algorithm's performance is better than the existing approaches. The energy prediction error of their algorithm is approximately 0.5%.

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Cited By

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Banotra AGhose SMishra DModem S(2023)Energy harvesting in self-sustainable IoT devices and applications based on cross-layer architecture designComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.110011236:COnline publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1016/j.comnet.2023.110011
Mindang ASiripongwutikorn P(2020)Solar Power Prediction in IoT Devices using Environmental and Location FactorsProceedings of the 2020 5th International Conference on Machine Learning Technologies10.1145/3409073.3409086(119-123)Online publication date: 19-Jun-2020
https://dl.acm.org/doi/10.1145/3409073.3409086

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Published In

IET Communications Volume 10, Issue 12

August 2016

142 pages

EISSN:1751-8636

DOI:10.1049/cmu2.v10.12

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John Wiley & Sons, Inc.

United States

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Published: 01 August 2016

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Banotra AGhose SMishra DModem S(2023)Energy harvesting in self-sustainable IoT devices and applications based on cross-layer architecture designComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.110011236:COnline publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1016/j.comnet.2023.110011
Mindang ASiripongwutikorn P(2020)Solar Power Prediction in IoT Devices using Environmental and Location FactorsProceedings of the 2020 5th International Conference on Machine Learning Technologies10.1145/3409073.3409086(119-123)Online publication date: 19-Jun-2020
https://dl.acm.org/doi/10.1145/3409073.3409086

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Energy harvesting discontinuous reception (DRX) mechanism in wireless powered cellular networks

Prediction free energy neutral power management for energy harvesting wireless sensor nodes

Energy-Harvesting Wireless Sensor Networks (EH-WSNs): A Review

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