Team Weekly Update | 4/19
Accomplishments
This week we made major progress on integrating the full sensing system onto the bike and preparing for the final presentation. Zoe completed the transition of the force sensing system onto protoboards and rewired everything to be cleanly mounted. Rita helped install the system onto the bike frame and made adjustments to the housing for better fit and wire management.
We also updated the calibration process to include a new pose and built a more robust matching system based on sensor masking and confidence scoring. We tested this while Rita rode the bike, including during active pedaling, and confirmed that the system worked reliably during motion.
Carolyn worked on syncing the app to the new system and added visual feedback features for pose matching. She and Zoe also made sure the app was installed and running on multiple devices for easier testing.
As a group, we started outlining our final presentation and discussed what visuals would help clearly explain how the hardware, software, and calibration all fit together.
Progress Status
The pressure sensor system is fully installed on the bike and working during ride tests. BLE communication with the app is functioning, and calibration logic has been verified in real-time. Housing iterations are progressing well, and the team is working together on app polish and presentation prep.
Next Steps
– Finish app integration with the new calibration structure
– Finalize mounting with updated 3D-printed housing
– Run additional rounds of riding tests to collect more data
– Test whether the system can function during a ride without the bike being mounted to the stand
– Continue refining slides and start creating visuals for the final presentation
– Begin reviewing earlier tests and compare against current system performance
Validation Plan
We validated the updated pressure sensor system during mounted ride testing, including with pedaling, and confirmed that the calibration logic held up under real-time conditions. The app is receiving and displaying BLE data from the ESP32 reliably.
Next, we want to run repeated ride tests to collect more data for analysis and refine our confidence matching logic. A key goal is to test whether we can use the system during a ride where the bike is not mounted, allowing for a more natural biking scenario. This will help us understand how the system behaves under more realistic user conditions, and whether stability or signal issues come up when the bike is in motion. We’ll also continue validating sensor response, BLE performance, and app visualization across devices.