This week, we made significant strides in both hardware tuning and software integration for the adaptive music bike system. The test version of the firmware was successfully updated to include three potentiometers, enabling real-time adjustment of the jump and drop detection thresholds. This allows for rapid fine-tuning during test rides without needing to reprogram the microcontroller, giving us more flexibility in calibrating sensor responsiveness. This marks a major step forward in making the system adaptable to different riding conditions and user preferences.
In parallel, we successfully completed the FMOD integration by linking sensor data to adaptive music parameters in the Android app. Using BLE, we now stream live data from the bike sensors—wheel speed, pitch angle, and detected events (like jump or drop)—directly into FMOD. These inputs modulate the corresponding FMOD parameters in real time, enabling dynamic music changes that respond to how the rider moves. This demonstrates the core functionality of the system and opens the door to further musical experimentation.
Next Steps:
- PCB
- We began the initial development of a custom PCB to replace our current perfboard-based setup. This move will consolidate components into a more compact, durable, and professional design suitable for long-term testing and potential deployment. The initial schematic and layout planning are underway, with plans to integrate the ESP32, sensor connectors, power regulation, and potentiometer inputs onto a single board.
- FMOD
- We also want to include multiple FMOD bank files that the user can choose from within the app. The goal is to give users the ability to choose from different adaptive soundscapes or musical styles depending on their mood or ride environment.
- Testing on the bike
- We are ready to gather data on the bike to fine tune the sensor range used for the adaptive music, but we will likely hold off on gathering data for the ML model until we finish the PCB board.
Music-Bike 
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