I did something similar, but because i had no requirement to playback audio "real time", i opted for a simpler solution. I run a simple video capture from a Ra

I did something similar, but because i had no requirement to playback audio "real time", i opted for a simpler solution. I run a simple video capture from a Raspberry Pi Zero W running motion, meaning all motion events are captured, including leaves blowing in the wind. The captured files are stored on a NFS share per camera. On the server i then monitor the parent directory for every camera for new files, and run my object detection there, which in turn generates push notifications with a screengrab if certain objects are detected. It also stores a bounding box annotated version of the file. Not really needed except for figuring out why you got an alert without any clear reason. doing it this way however allows me to save a bit on each camera, and use dedicated hardware for object detection on the server. I currently use an Intel Neural Compute Stick 2 (https://software.intel.com/content/www/us/en/develop/hardware/neural-compute-stick.html https://software.intel.com/content/www/us/en/develop/hardwar...), and while it is far from dedicated GPU performance, it is equally far from dedicated GPU power consumption.