A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology

Mengfei Xu; Yipeng Yang; Changqing Qiu

doi:10.1109/ICEMS59686.2023.10344414

A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology

Mengfei Xu^*
, Yipeng Yang
, Changqing Qiu

^*Corresponding author for this work

National Key Laboratory of Electromagnetic Energy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The underwater unmanned energy storage station has many special characters which caused communication limitations with the shore-based operation center that handles large amounts of data. It is necessary to design an independent on-site management system for the distributed underwater unmanned energy storage station maintenance system, which uses edge computing for real-time monitoring. Additionally, after the key data of stations were sent to shore-based operation center, the cloud computing technology and big data mining technology and AI (Artificial Intelligence) technology were used to predict and effectively schedule the operational status and trends of the energy storage stations, thereby improving the supply efficiency and operational life of the energy storage station cluster.

Original language	English
Title of host publication	2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5197-5202
Number of pages	6
ISBN (Electronic)	9798350317589
DOIs	https://doi.org/10.1109/ICEMS59686.2023.10344414
State	Published - 2023
Externally published	Yes
Event	26th International Conference on Electrical Machines and Systems, ICEMS 2023 - Zhuhai, China Duration: 5 Nov 2023 → 8 Nov 2023

Publication series

Name	2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023

Conference

Conference	26th International Conference on Electrical Machines and Systems, ICEMS 2023
Country/Territory	China
City	Zhuhai
Period	5/11/23 → 8/11/23

Keywords

AI
Management Systems
edge-cloud integration technology
unmanned energy storage stations

Access to Document

10.1109/ICEMS59686.2023.10344414

Cite this

Xu, M., Yang, Y., & Qiu, C. (2023). A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology. In 2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023 (pp. 5197-5202). (2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICEMS59686.2023.10344414

Xu, Mengfei ; Yang, Yipeng ; Qiu, Changqing. / A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology. 2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 5197-5202 (2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023).

@inproceedings{2064975ffd5c4e469129ac0777affbfa,

title = "A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology",

abstract = "The underwater unmanned energy storage station has many special characters which caused communication limitations with the shore-based operation center that handles large amounts of data. It is necessary to design an independent on-site management system for the distributed underwater unmanned energy storage station maintenance system, which uses edge computing for real-time monitoring. Additionally, after the key data of stations were sent to shore-based operation center, the cloud computing technology and big data mining technology and AI (Artificial Intelligence) technology were used to predict and effectively schedule the operational status and trends of the energy storage stations, thereby improving the supply efficiency and operational life of the energy storage station cluster.",

keywords = "AI, Management Systems, edge-cloud integration technology, unmanned energy storage stations",

author = "Mengfei Xu and Yipeng Yang and Changqing Qiu",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 26th International Conference on Electrical Machines and Systems, ICEMS 2023 ; Conference date: 05-11-2023 Through 08-11-2023",

year = "2023",

doi = "10.1109/ICEMS59686.2023.10344414",

language = "英语",

series = "2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "5197--5202",

booktitle = "2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023",

address = "美国",

}

Xu, M, Yang, Y & Qiu, C 2023, A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology. in 2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023. 2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023, Institute of Electrical and Electronics Engineers Inc., pp. 5197-5202, 26th International Conference on Electrical Machines and Systems, ICEMS 2023, Zhuhai, China, 5/11/23. https://doi.org/10.1109/ICEMS59686.2023.10344414

A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology. / Xu, Mengfei; Yang, Yipeng; Qiu, Changqing.
2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 5197-5202 (2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Xu, Mengfei

AU - Yang, Yipeng

AU - Qiu, Changqing

PY - 2023

Y1 - 2023

N2 - The underwater unmanned energy storage station has many special characters which caused communication limitations with the shore-based operation center that handles large amounts of data. It is necessary to design an independent on-site management system for the distributed underwater unmanned energy storage station maintenance system, which uses edge computing for real-time monitoring. Additionally, after the key data of stations were sent to shore-based operation center, the cloud computing technology and big data mining technology and AI (Artificial Intelligence) technology were used to predict and effectively schedule the operational status and trends of the energy storage stations, thereby improving the supply efficiency and operational life of the energy storage station cluster.

AB - The underwater unmanned energy storage station has many special characters which caused communication limitations with the shore-based operation center that handles large amounts of data. It is necessary to design an independent on-site management system for the distributed underwater unmanned energy storage station maintenance system, which uses edge computing for real-time monitoring. Additionally, after the key data of stations were sent to shore-based operation center, the cloud computing technology and big data mining technology and AI (Artificial Intelligence) technology were used to predict and effectively schedule the operational status and trends of the energy storage stations, thereby improving the supply efficiency and operational life of the energy storage station cluster.

KW - AI

KW - Management Systems

KW - edge-cloud integration technology

KW - unmanned energy storage stations

UR - https://www.scopus.com/pages/publications/85182318692

U2 - 10.1109/ICEMS59686.2023.10344414

DO - 10.1109/ICEMS59686.2023.10344414

M3 - 会议稿件

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T3 - 2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023

SP - 5197

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BT - 2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 5 November 2023 through 8 November 2023

ER -

Xu M, Yang Y, Qiu C. A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology. In 2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 5197-5202. (2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023). doi: 10.1109/ICEMS59686.2023.10344414

A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology

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Keywords

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