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Vicky’s Status Report for 3/15

Personal Accomplishments

  • Dash Cam Bringup & Testing:
    • Setted up Python virtual environment to run detection and OCR models with streaming Camera Module 3 input
    • Deployed and benchmarked ML license plate detection model on RPi 5, PyTorch format achieves around 370ms latency per frame, ONNX format achieves around 350ms latency per frame, and NCNN format achieves around 160ms latency per frame with streaming camera input
    • Deployed and benchmarked ML license plate OCR model on RPi 5, Paddle format achieves around 120ms latency per frame with streaming camera input, and ONNX format was deployed unsuccessfully
    • Wrote the end-to-end pipeline, with the main thread recording footage in 1 minute 480p20 clips, and the inference thread inferencing 2304*1296 resolution images and storing cropped license plate results at around 3fps

Progress

My progress is on schedule.

Schedule

  • GPS module bringup and testing
  • Network module bringup and testing
  • Opt-in switch module bringup and testing
  • End-to-end pipeline debugging
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Andy’s Status Report for 3/15

his week, I focused on planning power testing, discussing the web application, and beginning the Blues module bring-up by testing it on the RPi4.

To ensure a stable power supply for the RPi5, I developed a power testing plan. I researched various Uninterruptible Power Supply (UPS) HATs compatible with the RPi5 and placed an order. While waiting for delivery, I started planning the circuit testing process to ensure the module functions correctly and continues supplying power even when its main power source is turned off.

On the software side, I discussed with my team and Tamal the idea of not implementing a web portal but instead opting for a flexible and easier-to-implement API for user interaction.

Additionally, I began bringing up the Blues module, starting with initial tests on the RPi4 to verify communication and connectivity. I booted up the RPi4 and started integrating the Blues cellular chip with it.

Progress:

Overall, progress is on track. I have shifted my focus from the web app to assisting Vicky and Christine with dashcam and server implementation.

Schedule:

•Test the UPS module (if it arrives)

•Bring up the Blues module and test GPS

•Test uploading and receiving data from the server using the Blues chip on the RPi

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Christine’s Status Report for 3/1

Progress

  • Design Report Completed: Finalized and refined the system design after conducting additional AWS research. Key architectural changes were made based on our findings (see the team status report for details).
  • Updated Central Server Block Diagram: The design now reflects the latest refinements, ensuring clarity in system architecture. 
  • CI/CD Pipeline Implemented: Initially, I was manually setting up AWS services, but as the project grew, it became unsustainable. To streamline deployment, I set up a repository (Github Repo) with CI/CD (PR), which now automates testing and deployment. The folder structure is modular and designed for maintainability.
  • Watchlist Query Layer Implemented: A basic version (PR1 + PR2) is now complete and fully tested with manual tests + jest tests, though it currently operates without message queuing. The system generates and returns a pre-signed URL for secure data access.

In Progress

  • Web App Access Layer (Watchlist Management): Currently working on implementing this to allow the web app backend to post updates to the global watchlist. I’ve completed a basic implementation and tested it manually (draft PR).  I plan to add a Jest test suite for automated testing. My goal is to wrap this up as soon as possible so the web app can begin integrating with it.

Next Steps

  • Set Up Web App Backend Architecture: Set up a basic backend folder structure (controller, model, db, env) and implement a basic authentication endpoint to enable user login. Once completed, Andy will be able to take over further web app backend tasks.

Overall Status

  • The project remains on track. While the workload is demanding, the transition from manual AWS setup to automated CI/CD has significantly improved efficiency. Now, my focus is on completing the web app integration to ensure smooth interaction with the backend.
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Vicky’s Status Report for 3/1

Personal Accomplishments

  • Design Report:
    • Wrote and edited the design report
  • ML License Plate OCR:
    • Cleaned up platesmania.com dataset through script and manual inspection to improve training quality
    • Benchmarked a variety of OCR models and selected en_PP-OCRv3_rec model for its ease of integration with Python and lesser likelihood to overfit (93% accuracy on platesmania.com 80% synthetic + 20% real-world license plate dataset, 85% accuracy on platesmania.com 100% real-world license plate dataset)
  • ML End-To-End:
    • Designed, implemented, and tested the end-to-end script, achieving 81% end-to-end accuracy
  • Dash Cam Bringup & Testing:
    • Collaborated with Andy to bringup and test the RPi 5 board and camera module 3

Progress

My progress is on schedule.

Schedule

  • Single-board computer bringup and testing
  • Camera module bringup and testing
  • GPS module bringup and testing
  • Network module bringup and testing