Unlocking the Potential of AI-Powered Digital Twins in Advancing Space Technology

Dahiya, Ruby and Rajanarayanan, S. and Baskar, K. and Baig, Hidayath Ali (2024) Unlocking the Potential of AI-Powered Digital Twins in Advancing Space Technology. Springer. pp. 281-292. ISSN 2327-3275

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Abstract

The chapter provides an overview of the survey study that focuses on the synergistic potential of artificial intelligence (AI) and digital twins in the context of space technology. Digital twins, which are virtual replicas of physical systems or objects, have gained significant importance in the field of space technology. They serve as powerful tools for simulating and monitoring complex space missions, and when combined with AI technologies like machine learning and deep learning, they offer a wealth of opportunities for optimizing, automating, and improving space-related processes. In addition to highlighting the benefits, the survey also delves into the challenges and obstacles that researchers, engineers, and space agencies encounter while implementing AI-powered digital twins. These challenges encompass issues like data integration, model accuracy, and the computational demands of these sophisticated systems. © 2024 Elsevier B.V., All rights reserved.

Item Type: Article
Subjects: Engineering > Aerospace Engineering
Divisions: Medicine > Vinayaka Mission's Medical College and Hospital, Karaikal
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 27 Nov 2025 06:35
URI: https://vmuir.mosys.org/id/eprint/1686

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