After Receiving feedback on the design report, we decided to focus more on the cloud and front end part of the pipeline this week. I focused on building the cloud backend pipeline for the CALL ALPR dashcam system. I implemented a very minimal version of the serverless backend using Supabase Edge Functions and PostgreSQL. Specifically, I created the possible_matches table to store incoming data from the Raspberry Pi, including plate text, GPS location, image URL, and timestamps. I also worked on an Edge Function that receives HTTP POST requests from the RPi, parses the incoming data, and inserts it into the database. I also worked on the starter code for calling the edge function that will do ML inferencing. At this point, my progress is still on schedule. The cloud backend MVP has something which we can test and try to integrate with the Rpi. In the coming week, I plan to work with Richard to see if we can start getting actual data from the Rpi to the cloud. I’ll also add additional functionality to the front end to deal with the permissions for respective users.
