Soft robotics has gained significant attention for its ability to interact safely and adaptively with dynamic environments, offering promising applications in fields such as manufacturing and healthcare. However, precise real-time tracking and analysis of soft robotic motion remain challenging due to their highly deformable and nonlinear nature. Existing workflows for motion tracking often involve fragmented systems for data acquisition, transmission, and analysis, resulting in inefficiencies, delays, and synchronization issues. These challenges hinder the scalability and applicability of soft robotic systems in real-world scenarios. This study proposes a unified framework for real-time motion tracking and analysis of soft robotic arms, addressing the key issues of workflow integration and latency reduction. The system combines automated spatial data acquisition from a Polhemus sensor, low-latency UDP-based data transmission, and real-time visualization and processing in MATLAB/Simulink. Unlike traditional fragmented workflows, this approach eliminates the need for post-measurement data fusion by integrating acquisition, transmission, and analysis into a single pipeline.