{"id":76,"date":"2023-02-19T04:31:48","date_gmt":"2023-02-19T04:31:48","guid":{"rendered":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd4\/?p=76"},"modified":"2023-02-19T04:31:48","modified_gmt":"2023-02-19T04:31:48","slug":"team-status-report-2-18","status":"publish","type":"post","link":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd4\/2023\/02\/19\/team-status-report-2-18\/","title":{"rendered":"Team Status Report 2\/18"},"content":{"rendered":"

Summary\u00a0<\/span><\/h2>\n

Overall we made significant progress in designing our subsystems. We made a few design decisions that simplified our process, and we figured out what we could feasibly implement with the existing APIs. We were able to spend significant time at the Media Lab too which allowed us to work hands on with the lights, and control them effectively. Working on the design presentation together also gave us a lot more clarity into the inputs and outputs, and how we drive communication among the different subsystems.\u00a0<\/span><\/p>\n

Risks\u00a0<\/span><\/h2>\n

We were able to mitigate risks from the previous week i.e control the lights using a Python API directly, and not rely on QLC++ for light communication. However, we are still a little worried about the latency of the program as it is still real time, and we want to hit our target metric i.e <100ms of delay between the audio input and light being triggered. Other risks associated with the latency arise in the signal processing engine. In the signal processing engine, we are still a little confused about what coefficients related to the audio we will extract, and how we will use the current state, and eliminate a few possibilities using the spotify parameters of the song. This might be a computationally intensive problem as first we need to be able to generate all possible combinations, see what’s in the set of allowed combinations based on the genre, and remove from the set, and randomize options<\/span><\/p>\n

Changes\u00a0<\/span><\/h2>\n