AI-Powered Adaptive Frequency Antenna For Seamless Wireless Communication

Wireless communication systems today demand high reliability and adaptability as signal quality constantly varies due to interference, environmental obstacles, and user mobility. However, conventional fixed-frequency antennas lack the ability to adjust to such dynamic conditions, resulting in signal degradation, reduced coverage, and unstable communication. To address this limitation, this project proposes an AI-Powered Adaptive Frequency Antenna System capable of intelligently switching between multiple microstrip patch antennas tuned to 2.4 GHz, 3.7 GHz, and 5.5 GHz. A Software Defined Radio (SDR) module is used to capture real-time signal data, while a Raspberry Pi processes key parameters such as Received Signal Strength Indicator (RSSI) and Signal-to-Noise Ratio (SNR) using AI-based decision-making algorithms. Based on the analysis, the system automatically selects and activates the antenna that provides the best communication performance through a relay or RF switch. This adaptive approach ensures stable connectivity, improved signal quality, optimized bandwidth usage, and energy-efficient operation. The proposed system offers a low-cost, scalable, and intelligent solution suitable for applications such as IoT networks, smart infrastructure, mobile communication, and next-generation wireless systems.