Wireless communication is crucial for the modern technology, because it allows data to be sent seamlessly across a range of settings. However, communication in underwater situations is particularly difficult because of the physical characteristics of water, which greatly reduce the efficiency of conventional radio frequency (RF) signals. Therefore, underwater communication systems mainly rely on acoustic signals, which behave differently from RF signals in air. The project deals with a simulation and comparative study of underwater acoustic communication and RF communication with audio signals as input. The system was developed in Python and Flask and provides a web-based interface for users to upload audio files and visualize the transmission of signals over both communication channels.

The simulation models the real-world effects, such as noise, attenuation, multipath propagation, and signal distortion. The Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) are the performance measurements used to assess communication efficiency. The system is equipped with advanced signal processing techniques, such as Fast Fourier Transform (FFT) and Frequency Shift Keying (FSK) modulation, to analyze the frequency components and behavior of digital transmission. The project provides users with clear understanding of differences between Acoustic and RF communication systems, especially with regard to reliability, efficiency, and environmental constraints.

The system is intended as an educational tool for engineering students and researchers to learn the principles of wireless communication in a practical and interactive manner.

Keywords:

Underwater Acoustic Communication, RF Signal, FSK, Fast Fourier Transform (FFT), Python simulation, Audio Files, BER, SNR.