Ankita’s Status Report for 3/9/24

Work Done

Last week, I along with our group members worked on and completed our 12-page design report. I completed the design requirements, block diagrams, and summary, as well as the architectural, implementation, testing, and trade study descriptions of the camera interfacing with the Raspberry Pi and the object detection algorithm. To write the design report we had to flesh out many aspects of our project; we have decided to connect the RPi and IP cameras to a Mobile WiFi hotspot (I have an unlimited data plan, so cost will not be an issue). Connecting the RPi to CMU-DEVICE with a headless setup has proved to be difficult; I registered the MAC address with IT services but was unfortunately not able to ssh into the Pi’s network.

Schedule

Working on the design report took most of my time this week so I wasn’t able to train the new Haar classifier, though I have a better idea on how to do it now. I need some “negative” images to tag in order to train the classifier (images of intersections with 0 cars) so once I get back to Pittsburgh Zina and I will work on getting those taken. Because of this, I will probably simplify the pedestrian detection model to a simple “yes/no” classifier (as in, are there pedestrians waiting to cross?) instead of counting exactly how many pedestrians are on each side (since pedestrians tend to walk side by side when they cross anyway.) That way we can just use a pre-trained classifier or limit the accuracy of the classifier we do have.

Deliverables

By the end of next week, I will:

• Train the new vehicle classifier.
• Connect the RPi and the IP Cameras to the Mobile WiFi hotspot.
• Figure out what I need to do to capture an image with the BLE camera.