Quantum-Enhanced Cognitive AIoT for Real-Time Adaptive Decision-Making in Smart Infrastructure and Development for Industrial Deployment

Published: 28 July 2025| Version 1 | DOI: 10.17632/47gnfttgdx.1
Contributor:
Ahmed AYON

Description

The convergence of artificial intelligence (AI) with the Internet of Things (IoT) has transformed modern infrastructures into intelligent ecosystems capable of automated data collection and processing. The evolution toward Cognitive AIoT (CAIoT) introduces cognitive capabilities—memory, learning, reasoning, and contextual awareness—embedded within IoT edge devices, enabling autonomous decision-making.

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Quantum machine learning (QML) and quantum optimization algorithms, such as QAOA and Variational Quantum Eigensolvers (VQE), have shown promise in accelerating complex combinatorial problems and pattern recognition tasks. Federated quantum learning paradigms are emerging, yet integration into practical IoT systems remains nascent.

Institutions

  • Independent University
  • North South University

Categories

Quantum Computing, Adaptive Analysis, Cognitive Control, Federated Learning

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