Energy-Efficient Wireless Power Transfer System for IoT Devices

Low energy efficiency, misalignment-induced energy loss, limited range, and sensitivity to external variables describe Wireless Power Transfer (WPT) solutions for Internet of Things (IoT) devices. Traditional methods include inductive and RF-based WPT with uneven power distribution in dynamic environments and proximity restrictions. The proposed system dynamically changes transmission parameters and combines adaptive resonance tuning and beamforming to improve energy economy, range, and stability using machine learning (ML) for real-time adaptation. Simulation and experimental results reveal considerable increases in power transmission efficiency with the proposed system obtaining up to 95% efficiency at 1 meter compared to 82% and 88% in the existing systems. Energy loss at 1 meter is 0.15 W; at 7 meters, stability gains from just an 8% fluctuation in power output. The results provide a feasible substitute for sustainable wireless power transfer and prove the brilliance of the proposed system in long-range and dynamic IoT applications.