AI-Driven Techniques for Secure Smart Systems and Intelligent Infrastructure: A Survey and Integrated Framework

  • Unique Paper ID: 183355
  • Volume: 12
  • Issue: 3
  • PageNo: 1020-1030
  • Abstract:
  • The convergence of artificial intelligence, machine learning, and advanced computational models has significantly transformed modern digital ecosystems, enhancing applications across domains such as smart homes, image forensics, cybersecurity, intelligent travel planning, and healthcare support. Emerging techniques such as genetic algorithms, wavelet transforms, fuzzy grouping, and deep learning models have enabled robust solutions for virtual machine placement, biometric authentication, image forgery detection, and cyberbullying detection. This paper presents a comprehensive exploration of recent developments in AI-driven strategies, including dynamic pricing optimization [1], secure biometric systems [12], and blockchain-enabled agri-food supply chains [6]. The integration of algorithms such as support vector machines, glow-worm optimization, and convolutional neural networks (CNNs) into practical applications has led to performance improvements across multiple sectors [10], [11], [16]. The study further examines innovative tools like AI-based trip planners [8] and Alzheimer's patient support apps [13], emphasizing the critical role of intelligent system design in addressing real-world challenges. Through an in-depth analysis of 23 recent scholarly works, this research highlights key technological trends, implementation outcomes, and future trajectories for scalable AI systems.

Cite This Article

  • ISSN: 2349-6002
  • Volume: 12
  • Issue: 3
  • PageNo: 1020-1030

AI-Driven Techniques for Secure Smart Systems and Intelligent Infrastructure: A Survey and Integrated Framework

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