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<p>The Sustainable Monitoring &amp; Advanced Real-Time Energy Efficiency (SMARTEE) project addresses the critical challenge of optimizing energy management in pharmaceutical manufacturing through an Industrial Internet of Things (IIoT)-based submetering solution. This study presents the design and deployment of a tailored IoT system, integrating IoT-enabled submeters, a Mini-PC gateway, and cloud-based analytics for continuous, real-time energy consumption monitoring across critical equipment such as chillers, boilers, and HVAC systems. Following a systematic methodology, the project implemented advanced data acquisition and communication protocols, including Modbus over RS485, Node-RED for data processing, and MQTT for transmitting energy metrics to a cloud-based visualization platform. Results demonstrated the system’s efficacy in delivering actionable insights into energy patterns, significantly improving operational efficiency and waste reduction. The IoT-based solution is highly scalable, adaptable to various industrial contexts, and provides a secure platform for real-time monitoring. This work highlights the potential of IoT in transforming industrial energy management, with future research focusing on AI-driven predictive analytics and seamless integration with renewable energy systems to enhance sustainability and resilience further.</p>

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Industrial IoT-based submetering solution for real-time energy monitoring

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月22日

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  • Hussam J. Khasawneh,
  • Raghad Al Asbahi,
  • Abdelrahman W. Alzariqi,
  • Danah R. Al Qada,
  • Ayman Bujuk,
  • Muhammad A. Nawfal,
  • Maria Tareen

摘要

The Sustainable Monitoring & Advanced Real-Time Energy Efficiency (SMARTEE) project addresses the critical challenge of optimizing energy management in pharmaceutical manufacturing through an Industrial Internet of Things (IIoT)-based submetering solution. This study presents the design and deployment of a tailored IoT system, integrating IoT-enabled submeters, a Mini-PC gateway, and cloud-based analytics for continuous, real-time energy consumption monitoring across critical equipment such as chillers, boilers, and HVAC systems. Following a systematic methodology, the project implemented advanced data acquisition and communication protocols, including Modbus over RS485, Node-RED for data processing, and MQTT for transmitting energy metrics to a cloud-based visualization platform. Results demonstrated the system’s efficacy in delivering actionable insights into energy patterns, significantly improving operational efficiency and waste reduction. The IoT-based solution is highly scalable, adaptable to various industrial contexts, and provides a secure platform for real-time monitoring. This work highlights the potential of IoT in transforming industrial energy management, with future research focusing on AI-driven predictive analytics and seamless integration with renewable energy systems to enhance sustainability and resilience further.