On Predicting the Battery Lifetime of IoT Devices

Author:

Fafoutis Xenofon1,Elsts Atis2,Vafeas Antonis2,Oikonomou George2,Piechocki Robert2

Affiliation:

1. Technical University of Denmark, Kgs. Lyngby, Denmark

2. University of Bristol, Bristol, UK

Publisher

ACM

Cited by 27 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Energy Harvesting and Storage Solutions for Low-Power IoT Devices in Livestock Industry;2024 IEEE 15th Latin America Symposium on Circuits and Systems (LASCAS);2024-02-27

2. Use of Deep Neural Networks to Predict Lithium-Ion Cell Voltages During Charging and Discharging;2023 IEEE Region 10 Symposium (TENSYMP);2023-09-06

3. Role of Battery Management System in IoT Devices;Smart Grids and Internet of Things;2023-04-28

4. Ultra-Fast and Efficient Design Method Using Deep Learning for Capacitive Coupling WPT System;IEEE Transactions on Power Electronics;2023

5. Estimating SoC, SoH, or RuL of Rechargeable Batteries via IoT: A Review;IEEE Internet of Things Journal;2023

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