AI-Based Optimal Energy Harvesting to Reduce Electromagnetic Radiation from GSM and WiFi at ATBU Yalwa Campus

Abstract

The tuning of LC impedance matching networks for Wireless Power Transfer (WPT) systems and the optimisation of Microstrip Patch Antennas (MPAs) are thoroughly examined in this work. A workable approach that achieves dependable convergence without requiring intricate mathematical modelling is put forth. This study examined the health hazards linked to rising mobile phone use and the positioning of mobile base stations in Nigeria's most populated regions. At the Abubakar Tafawa Balewa University (ATBU) Yelwa campus, measurements of power density, electric field strength, and magnetic field strength were made using TM-195 meter technology and OpenSignal software. Within 16.48 meters of the main coverage area, power density values were found to exceed the permitted limit of 0.001 W/m² by up to 4.81 times, posing serious health and safety risks to the local population. Additionally, it was shown that scavenging low-density RF signals from 0.5 to 3 GHz is feasible. At a resonant frequency of 1.8 GHz, optimised rectenna designs achieved peak voltages of 1.2 V and peak currents of 120 μA. The measurement setup indicates that the rectifier achieves 69.4% efficiency at +10 dBm, 20% from +5 dBm to +13 dBm, with output voltages ranging from 27.9 mV to 104.1 mV. Harvesting energy in the form of power to supply loads of the required rating allowed for a 99.88% power reduction, reducing 7,583.55 µW from the TM-195's maximum of 5810 µW to a simulated 306.38 µW. By lowering exposure to electromagnetic radiation, this optimisation improved energy efficiency and preserved operational efficacy while lowering possible health risks.