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A Requirement-Driven Digital Twin Data Fusion Framework

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A structured requirements-driven digital twin data fusion framework for enhancing interoperability, scalability and adaptability across diverse cyber physical system applications is designed and developed in this research. Digital twins are now indispensable for real time synchronization, predictive analytics and operational decision making across many industries including manufacturing, healthcare and infrastructure management. However, digital twins are still facing several implementation challenges, including standardization gaps, interoperability constraints and computational limitations. This Praxis systematically integrates principles of requirements engineering with advanced data fusion methodologies with the aim of explicitly linking stakeholder defined needs to digital twin system functionalities. By developing and validating the methods through targeted case studies, the proposed framework is shown to enhance system interoperability, adaptability, scalability, and lifecycle management to a greater extent than current practices in digital twin applications of Industry 4.0 ecosystems.

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