Cloud-Based Monitoring and Management Platform for Electrical Equipment

The article suggests a cloud-based monitoring and managerial system for electrical devices that combines data collection, status tracking, and intelligent decision-making functionalities. The system design uses a three-tier architecture with a data collection layer, a cloud service layer, and an application layer, employing digital twin technology for equipment status monitoring and prediction. A generic data schema is implemented to accommodate non-relational data sources, while a distributed data storage system architecture provides high availability and system scalability. The automated intelligent management system employs various AI algorithms for automated decision-making, enabling optimal maintenance resource scheduling and management. During the testing of the system, data was collected over a 3-month period using 50 electrical devices. The system performed reliably with response times of less than 100 ms and a 94.5% fault detection rate. The system proved to be more efficient as it decreased equipment downtime by 35% relative to the traditional approach. The system passed the accuracy and effectiveness tests, which in turn improved monitoring and management of the electrical devices. These efforts will help advance smart grid technology and provide a modern answer to managing electronic devices.

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Publication Details

Published
2025-06-28
DOI
https://doi.org/10.1109/icipca65645.2025.11138900
Primary Topic
Power Systems and Technologies
Type
article
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article

Cloud-Based Monitoring and Management Platform for Electrical Equipment

Yang Zhang, Lixiang Wang, Li Yunyang
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Power Systems and Technologies
article

Cloud-Based Monitoring and Management Platform for Electrical Equipment

Yang Zhang, Lixiang Wang, Li Yunyang
article en

Abstract

The article suggests a cloud-based monitoring and managerial system for electrical devices that combines data collection, status tracking, and intelligent decision-making functionalities. The system design uses a three-tier architecture with a data collection layer, a cloud service layer, and an application layer, employing digital twin technology for equipment status monitoring and prediction. A generic data schema is implemented to accommodate non-relational data sources, while a distributed data storage system architecture provides high availability and system scalability. The automated intelligent management system employs various AI algorithms for automated decision-making, enabling optimal maintenance resource scheduling and management. During the testing of the system, data was collected over a 3-month period using 50 electrical devices. The system performed reliably with response times of less than 100 ms and a 94.5% fault detection rate. The system proved to be more efficient as it decreased equipment downtime by 35% relative to the traditional approach. The system passed the accuracy and effectiveness tests, which in turn improved monitoring and management of the electrical devices. These efforts will help advance smart grid technology and provide a modern answer to managing electronic devices.

China Three Gorges Corporation (China) (CN), China Three Gorges University (CN)
Openalex Percentile: Top 77%
Power Systems and Technologies
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Cloud-Based Monitoring and Management Platform for Electrical Equipment — Yang Zhang, Lixiang Wang, et al. · (2025) | TGRS Research Map | TGRS