UAV and IoT-Based Systems for the Monitoring of Industrial Facilities Using Digital Twins: Methodology, Reliability...

Area of Science:

• Engineering
• Computer Science
• Industrial Automation

Background:

• Industrial facilities require robust monitoring systems for safety and operational efficiency.
• Existing systems may lack resilience against component failures and diverse operational conditions.
• Integration of advanced technologies is crucial for next-generation industrial monitoring.

Purpose of the Study:

• To propose a methodology for designing reliable and resilient two-mode monitoring systems (SMs) for industrial facilities.
• To leverage unmanned aerial vehicle (UAV), Internet of Things (IoT), and digital twin (DT) technologies for enhanced monitoring.
• To develop reliability models for these advanced SMs.

Main Methods:

• Application of the von Neumann paradigm for synthesizing reliable systems from potentially unreliable components.
• Implementation of various redundancy types (structural, version, time, space) for core SM components.
• Development of multi-level SM structures integrating UAV, IoT, and DT technologies.

Main Results:

• A comprehensive methodology for building UAV-, IoT-, and DT-based SMs for industrial facilities.
• Reliability models tailored for SMs incorporating these technologies and considering normal/emergency modes.
• Demonstrated industrial cases for manufacturing and nuclear power plants.

Conclusions:

• The proposed methodology provides a framework for constructing resilient SMs for industrial environments.
• The developed reliability models are essential for assessing and ensuring SM performance.
• This research supports the advancement of Industry 4.0 principles through integrated monitoring solutions.