This document introduces a comprehensive proposal for advancing the development of diagnostic tools designed to model underwater channel conditions dynamically. The primary objective is to furnish pertinent insights to enhance the efficacy of existing channel equalization systems utilized by the United States Navy. Our envisioned solution involves implementing a cutting-edge system by employing hardware-software co-design methodologies on a Multi-Processor System-on-Chip based on Field-Programmable Gate Array (FPGA) technology (MPSoC). The inherent advantages of the MPSoC architecture lie in its capacity to facilitate algorithm parallelization and seamless interaction with other hardware systems via high-speed transceivers, all while maintaining an intuitive and user-friendly interface at the software level. To accurately represent underwater channel dynamics, we propose a multifaceted approach that integrates time-frequency computational tools with machine learning techniques. The emphasis is on selecting techniques with high parallelism and minimal computational overhead, ensuring real-time implementation feasibility