Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/642067
Title: An IoT-Based Online Monitoring System for Continuous Steel Casting
Authors: Feng Zhang;Min Liu;Zhuo Zhou;Weiming Shen
subject: Internet of Things (IoT)|Continuous steel casting|data processing|online monitoring
Year: 2016
Publisher: IEEE
Abstract: Monitoring solutions using the Internet of Things (IoT) techniques, can continuously gather sensory data, such as temperature and pressure, and provide abundant information for a monitoring center. Nevertheless, the heterogeneous and massive data bring significant challenges to real-time monitoring and decision making, particularly in time-sensitive industrial environments. This paper presents an online monitoring system based on an IoT system architecture which is composed of four layers: 1) sensing; 2) network; 3) service resource; and 4) application layers. It integrates various data processing techniques including protocol conversion, data filtering, and data conversion. The proposed system has been implemented and demonstrated through a real continuous steel casting production line, and integrated with the TeamCenter platform. Results indicate that the proposed solution well addresses the challenge of heterogeneous data and multiple communication protocols in real-world industrial environments.
Description: 
URI: http://localhost/handle/Hannan/175809
http://localhost/handle/Hannan/642067
ISSN: 2327-4662
volume: 3
issue: 6
Appears in Collections:2016

Files in This Item:
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Title: An IoT-Based Online Monitoring System for Continuous Steel Casting
Authors: Feng Zhang;Min Liu;Zhuo Zhou;Weiming Shen
subject: Internet of Things (IoT)|Continuous steel casting|data processing|online monitoring
Year: 2016
Publisher: IEEE
Abstract: Monitoring solutions using the Internet of Things (IoT) techniques, can continuously gather sensory data, such as temperature and pressure, and provide abundant information for a monitoring center. Nevertheless, the heterogeneous and massive data bring significant challenges to real-time monitoring and decision making, particularly in time-sensitive industrial environments. This paper presents an online monitoring system based on an IoT system architecture which is composed of four layers: 1) sensing; 2) network; 3) service resource; and 4) application layers. It integrates various data processing techniques including protocol conversion, data filtering, and data conversion. The proposed system has been implemented and demonstrated through a real continuous steel casting production line, and integrated with the TeamCenter platform. Results indicate that the proposed solution well addresses the challenge of heterogeneous data and multiple communication protocols in real-world industrial environments.
Description: 
URI: http://localhost/handle/Hannan/175809
http://localhost/handle/Hannan/642067
ISSN: 2327-4662
volume: 3
issue: 6
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7544510.pdf1.63 MBAdobe PDFThumbnail
Preview File
Title: An IoT-Based Online Monitoring System for Continuous Steel Casting
Authors: Feng Zhang;Min Liu;Zhuo Zhou;Weiming Shen
subject: Internet of Things (IoT)|Continuous steel casting|data processing|online monitoring
Year: 2016
Publisher: IEEE
Abstract: Monitoring solutions using the Internet of Things (IoT) techniques, can continuously gather sensory data, such as temperature and pressure, and provide abundant information for a monitoring center. Nevertheless, the heterogeneous and massive data bring significant challenges to real-time monitoring and decision making, particularly in time-sensitive industrial environments. This paper presents an online monitoring system based on an IoT system architecture which is composed of four layers: 1) sensing; 2) network; 3) service resource; and 4) application layers. It integrates various data processing techniques including protocol conversion, data filtering, and data conversion. The proposed system has been implemented and demonstrated through a real continuous steel casting production line, and integrated with the TeamCenter platform. Results indicate that the proposed solution well addresses the challenge of heterogeneous data and multiple communication protocols in real-world industrial environments.
Description: 
URI: http://localhost/handle/Hannan/175809
http://localhost/handle/Hannan/642067
ISSN: 2327-4662
volume: 3
issue: 6
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7544510.pdf1.63 MBAdobe PDFThumbnail
Preview File