Efficient sensing and autonomous decision-making in large-scale environments face challenges such as sensor noise, limited coverage, and dynamic environmental changes, often leading to suboptimal responses. This study proposes an AI-driven framework that integrates multi-sensor data fusion, adaptive learning, and utili...
F. Philip-Kpae, A. Imoize, Lloyd Endurance Ogbondamati et al.· E3S Web of Conferences· 0 citations
A lightweight edge AI framework that employs federated learning, enabling model training across distributed Internet of People and Things (IoP) devices without transferring raw data to centralised servers is proposed, enabling responsive, privacy-preserving, and resilient edge AI operations in distributed environments.
F. Philip-Kpae, A. Imoize, Lloyd Endurance Ogbondamati et al.· E3S Web of Conferences· 0 citations
An AI-assisted, cross-layer security orchestration framework that integrates epoch-wise telemetry with ML-based risk estimation and formalizes mitigation as a Constrained Markov Decision Process (CMDP), and empirical evidence that adaptive mitigation can reduce security risk without sacrificing service guarantees is pr...
F. Philip-Kpae, A. Imoize, K. .. Okafor et al.· E3S Web of Conferences· 0 citations
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