Developed a hardware-oriented fitness tracking feature for the Automation-Course/Automation_Course_2025B repository, focusing on autonomous workout management and real-time user feedback. Designed and implemented Arduino-based firmware in C++ that initializes and manages LCD displays, buttons, PIR sensors, LEDs, and buzzers to support interactive workout sessions. The solution integrates motion detection and provides user feedback through melodies and beeps, enabling hands-free operation directly on the device. Organized the firmware repository structure to streamline asset management and support future scalability. Demonstrated core skills in embedded systems, Arduino hardware interfacing, and IoT, delivering a modular and maintainable approach to on-device fitness tracking.