Milestone 4

Optimization

Software & Code

Optimizations made:

Moved from static plotting of saved data to live plotting of sensor data on an interface
Data collected by the Raspberry Pi and the XAIO Sense Microcontroller stored in a comma separated list
- Not yet encrypted
Prevented graph overflow by only displaying 50 most recently captured data points
Prevented overflow error with any negative numbers being transmitted to the Raspberry Pi through offset value

Electrical Circuits

Optimizations made:

Went from using 4 Op-Amps to using 2 Op-Amps
- We are using the JRC4558 Dual Op-Amp as seen in Figure 3
Went from having resistors, wires, and diodes on our breadboard being very tall and poking out to having it be very flat and slim
- We trimmed the prongs on resistors and diodes and use flat wires with short prongs
- The final breadboard iteration can be seen in Figure 5
Went through 3 iterations of custom PCBs
- First iteration was with 4 Op-Amps, 2 layers, and 42 x 42 mm (Figure 8)
- Second iteration was with 2 Op-Amps, 2 layers, and 45 x 45 mm (Figure 9)
- Third iteration is the same as the second one with smaller dimensions of 37 x 32 mm (Figure 10)

Figure 1: Arduino IDE Serial Monitor Output

XIAO BLE Microcontroller Sensors Side

(triangle wave test data)

Figure 2: Plot Output of Received Data

Raspberry Pi 4 Model B Interface Side

Figure 3: JRC4558 Dual Op-Amp Pinout

Delivery

Hardware

Figure 4: Simulink Diagram of Circuit

Figure 5: Amplifier Circuit, without a dual Op-Amp

Figure 6: High Pass Filter

Figure 7: Top View of Completed Circuit with XIAO Sense Microcontroller

Figure 8: PCB Iteration 1

Figure 9: PCB Iteration 2

Figure 10: PCB Iteration 3

Software

Figure 11: XIAO Sense BLE Microcontroller Code

Sends sensor data from the XIAO BLE microcontroller (Figure 12) to Raspberry Pi 4 Model B (Figure 13) used as interface through Bluetooth (XiaoWaveform2.ino)

Figure 12: XIAO Sense BLE Microcontroller

Figure 13: Raspberry Pi 4 Model B

Raspberry Pi 4 Model B Interface Code

Figure 14: receive_waveform2.py code file: Record data for 10 seconds, then display

Figure 15: receive_waveform3.py code file: Live plotting is added; program runs for 10 seconds, updating the graph with each new sensor input

Figure 16: receive_waveform4.py code file: Data storage implemented and graph overflow solved; writes sensor data to a .csv file that a separate program, display_waveform.py, uses to live plot the sensor inputs

Figure 17: display_waveform.py code file: Runs concurrently with receive_waveform4.py, displaying 50 most recently recorded sensor values on an updating graph; live plots sensor data

Live Testing Video

IMG_9556.MOV

Screenshots of Live Data Transmission

Innovation Expo Poster

Management

We evaluated each team member on the following categories on a scale from 1 (bad) to 5 (good):

Participation
Timeliness
Communication
Development of Product
Overall Contribution

The results can be seen in the following image carousel:

Overall, the team believes that the project was successful, but there are areas for improvement. More research on compatible microcontrollers earlier on could have streamlined the process, potentially allowing us to purchase a custom PCB. Working with friends had its challenges, with conflicts that could have been avoided or managed better due to the different dynamic of working relationships. Despite these challenges, we felt the project achieved more than expected, especially after overcoming hurdles like data transfer via Bluetooth. Our team wished for an overall more appealing and compact design with a physical casing but time constraints played a factor in this failure, particularly with software development. Despite not fully realizing certain aspects like a physical model, our team believed we managed our time effectively and adapted well to initial setbacks in code development and data transmission by focusing on PCB and circuit design preparation for seamless incorporation and testing.