AI-Driven Cloud Lifecycle Framework for Risk-Aware Cybersecurity in Wireless BMS Using SVM
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Abstract
This paper presents an Intelligent Cloud Lifecycle Architecture that integrates Support Vector Machine (SVM) algorithms and Wireless Building Management Systems (BMS) to enhance cybersecurity, operational intelligence, and adaptive control in smart infrastructures. The proposed framework leverages AI-driven analytics to monitor, predict, and mitigate cyber threats across the cloud lifecycle while ensuring seamless interoperability between IoT-enabled wireless nodes and centralized management systems. By combining SVM-based intrusion detection with dynamic cloud orchestration, the system achieves optimized energy usage, improved fault tolerance, and real-time risk assessment. The architecture supports scalable deployment, predictive maintenance, and continuous learning for sustainable and secure building ecosystem modernization.
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