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Author:

Sun, Jialan (Sun, Jialan.)

Indexed by:

EI Scopus

Abstract:

Coal is a prominent energy resource for several countries. Of late, exploring the automatic management and control of coal mining has been a significant task. This article presents a framework for a mine-wide integrated automation management and control platform with the goal of advancing coal mining through unified data, models, platforms, and plans. Utilizing cutting-edge technologies, the platform offers resource management, real-time monitoring, remote control, statistical analysis, and intelligent alarm systems. Data access design ensures standardized data collection and exchange, fostering interoperability. A big data storage center manages heterogeneous data sources. The platform interface design emphasizes flexibility and scalability through containerized applications and microservices frameworks, streamlining deployment. The functional design encompasses subsystem configuration access, real-time monitoring, remote access, etc. A detailed evaluation is presented to demonstrate the significance of the proposed platform in terms of functionality, performance, and scalability. © 2024 IGI Global. All rights reserved.

Keyword:

Coal Information management Scalability Alarm systems Real time systems Remote control Coal deposits Digital storage Coal mines Coal storage Big data

Author Community:

  • [ 1 ] [Sun, Jialan]College of Mechanical & Energy Engineering, Beijing University of Technology, China
  • [ 2 ] [Sun, Jialan]Ccteg China Coal Research Institute, China
  • [ 3 ] [Sun, Jialan]Engineering Research Center for Technology Equipment of Emergency Refuge in Coal Mine, Beijing, China
  • [ 4 ] [Sun, Jialan]Beijing Mine Safety Engineering Technology Research Center, Beijing, China

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Source :

International Journal of Distributed Systems and Technologies

ISSN: 1947-3532

Year: 2024

Issue: 1

Volume: 15

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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