This study introduces a lightweight, efficient, and secure architecture designed for the remote monitoring and control of Programmable Logic Controllers (PLCs). The proposed system uses the Open Platform Communications Unified Architecture (OPC UA) protocol to establish a standardized communication with a Raspberry Pi serving as an edge client able to interface industrial PLCs with other systems, facilitating both remote data acquisition and control operations. The collected data is synchronized with a real-time database, facilitating remote access through a mobile application as a human machine interface. This setup supports bidirectional communication, allowing for both monitoring and command issuance through the cloud. The proposed architecture offers a cost-effective alternative to traditional SCADA systems by emphasizing modularity, adaptability, low power consumption, real-time visualization, and cloud accessibility. Experimental evaluations demonstrate the system’s responsiveness, reliability, and applicability in both industrial and educational environments.

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Remote Industry Supervision on Mobile Application Based on OPC UA Protocol

  • Hadjer Bouzebiba,
  • Oussama Hadj Abdelkader,
  • Fernando Fontes

摘要

This study introduces a lightweight, efficient, and secure architecture designed for the remote monitoring and control of Programmable Logic Controllers (PLCs). The proposed system uses the Open Platform Communications Unified Architecture (OPC UA) protocol to establish a standardized communication with a Raspberry Pi serving as an edge client able to interface industrial PLCs with other systems, facilitating both remote data acquisition and control operations. The collected data is synchronized with a real-time database, facilitating remote access through a mobile application as a human machine interface. This setup supports bidirectional communication, allowing for both monitoring and command issuance through the cloud. The proposed architecture offers a cost-effective alternative to traditional SCADA systems by emphasizing modularity, adaptability, low power consumption, real-time visualization, and cloud accessibility. Experimental evaluations demonstrate the system’s responsiveness, reliability, and applicability in both industrial and educational environments.