An Integrated Framework for Intelligent Healthcare and Industrial Systems using AI and SDN NFV Enabled Cloud Network Architectures and Privacy Preserving Security
DOI:
https://doi.org/10.15680/IJCTECE.2021.0404006Keywords:
Artificial Intelligence, SDN, NFV, Cloud Computing, Intelligent Healthcare, Industrial Systems, Privacy-Preserving Security, Cyber-Physical Systems, Network ScalabilityAbstract
The rapid evolution of intelligent healthcare and industrial systems has introduced complex challenges related to scalability, reliability, security, and data privacy. Emerging technologies such as artificial intelligence (AI), software-defined networking (SDN), network function virtualization (NFV), and cloud computing offer promising solutions, yet their isolated adoption limits overall system effectiveness. This paper proposes an integrated framework that unifies AI-driven analytics, SDN/NFV-enabled cloud networks, and privacy-preserving security mechanisms to support intelligent, scalable, and resilient healthcare and industrial applications. The framework enables real-time decision-making, adaptive network management, secure data exchange, and efficient resource utilization across heterogeneous cyber-physical environments. AI models enhance predictive analytics, anomaly detection, and operational optimization, while SDN and NFV provide flexible and programmable network control. Privacy-preserving security techniques ensure data confidentiality and integrity without compromising system performance. The proposed architecture is designed to handle dynamic workloads, mission-critical communication, and large-scale data processing demands. This study contributes a holistic approach that addresses both technological and operational requirements, offering a foundation for next-generation intelligent systems capable of supporting healthcare delivery, industrial automation, and critical infrastructure services in cloud and 5G-enabled environments.
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