Plant-level IIOT-based Energy Management Framework with Cybersecurity Protection
Plant-level IIOT-based Energy Management Framework with Cybersecurity Protection
Primary researcher: Liya Elizabeth Koshy, Ph.D. candidate
This project introduces a scalable cloud-based solution that seamlessly integrates business analytics with sensor data for real-time energy management at the plant level. The platform not only facilitates comprehensive monitoring and analysis but also enables remote equipment control, leading to enhanced operational efficiency and energy savings.
Key features:
- Adaptability Across Industries: The solution is engineered for high adaptability, making it suitable for small and medium-sized companies across various industries. It requires minimal customization, ensuring a streamlined deployment process and quick implementation.
- Integrated Sensor Network: A diverse array of sensors, including current sensors, temperature sensors, carbon dioxide sensors, and pressure sensors, is seamlessly integrated into the system. This integration captures detailed data on facility performance and energy consumption, enabling precise analysis and actionable insights.
- Real-Time Monitoring and Control: Users can access real-time data on equipment performance and energy usage trends, empowering proactive identification of issues and optimization opportunities. The platform also enables remote control of equipment, providing flexibility and responsiveness to operational needs.
- Seamless Integration and Accessibility: The platform offers seamless integration with other applications and models, allowing energy engineers to incorporate prediction and recommendation models effortlessly. This integration enhances analytical capabilities and expands the platform?s utility across diverse use cases. Secure accessibility to data based on user privileges ensures data security and privacy while offering a user-friendly interface for data analysis.
The solution has undergone rigorous testing and validation, demonstrating its reliability, accuracy, and scalability. It has been successfully implemented in various settings, including manufacturing plants, lecture hall, and testbed, showcasing its effectiveness in real-world applications.
Ongoing Research Focus:
Continuing research focuses on implementing a Digital Twin for energy management strategy simulation and execution. These advancements further enhance the system?s capabilities and support continuous energy auditing and management.
