AI-Driven Adaptive Anomaly Detection and Control for IoT Cyber-Physical Systems

Author(s)	Mr. Prudvi Saisaran Ponduru
Country	India
Abstract	This paper proposes ADAPT-IoT, an AI-driven adaptive control framework for secure and resilient Internet-of-Things cyber-physical systems. The framework integrates edge inference, anomaly detection, predictive analytics, security risk assessment, feedback control, cloud coordination, and human supervision. A discrete-time dynamical model is formulated with disturbance and anomaly terms. The contribution is theoretical and architectural, providing a mathematically grounded framework for real-time resilient control without claiming empirical results.
Keywords	Artificial Intelligence, Internet of Things, Cyber-Physical Systems, Dynamical Systems, Control Systems, Anomaly Detection, Machine Learning, Edge AI, Predictive Control, Cybersecurity
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-06-10
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.81048

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