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AI-Twin: AI-Powered Digital Twin for Personalized Assistance and Predictive Decision- Making

Author

Listed:
  • Dr. Karthi Govindharaju

    (Artificial Intelligence and Data Science Saveetha Engineering College Chennai, India)

  • Janani R

    (Artificial Intelligence and Data Science Saveetha Engineering College Chennai, India)

  • Dr. Rajarajachozhan C

    (Electronics and Communication Engineering Saveetha Engineering College, Chennai, India)

  • Mirudhula D

    (Artificial Intelligence and Data Science Saveetha Engineering College Chennai, India)

Abstract

AI-driven digital assistants are vital for automating operations and optimizing user interactions, but current systems tend to lack adaptability, contextuality, and real-time learning. AI Twin is a future-generation digital twin created with the intent of personalized assistance and predictive decision-making. With the use of reinforcement learning, it learns and adjusts to user actions in real-time, fine-tuning responses and enhancing decision-making capabilities with the passage of time. As opposed to traditional AI assistants, AI Twin focuses on privacy using local data processing, minimizing cloud dependency while ensuring security. The platform combines natural language processing, speech recognition, and multi-agent learning to improve personalization and automation in different domains, such as smart environments and real-time decision support. This paper introduces AI Twin architecture, contrasts it with current AI technology, and delineates its prospect to drive forward AI- based user support.

Suggested Citation

  • Dr. Karthi Govindharaju & Janani R & Dr. Rajarajachozhan C & Mirudhula D, 2025. "AI-Twin: AI-Powered Digital Twin for Personalized Assistance and Predictive Decision- Making," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 12(3), pages 609-617, March.
    • Handle: RePEc:bjc:journl:v:12:y:2025:i:3:p:609-617
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