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IoT

Birbicam.

When I posted that video on IG, I knew I wanted to come back to it. My mechanics of capturing that story was a bit precarious: I propped my phone up on a rock, and hoped that in the video being captured, a bird or two would feature before I ran out of space.

So then I saw Alex Ellis’ tweet about using an RPi to track plant growth and I remembered I had a Raspberry Pi just lying there, waiting to get used.

Thus, my mind went into overdrive. I started to focus on the hardest part of the mini-project: Bird detection using Python or Tensor Flow on the Raspberry Pi. I hadn’t even turned the thing on yet. No OS installed. I didn’t even know if those super cheap sports cameras I had lying around would work.

I just mentally swam around in the deep setup, maybe even going to get some OpenCV involved.

Eventually, I calmed down. And began the pedestrian work of setting up the Pi, finding a working camera and getting the networking right.

When I had everything all put together, I cracked my knuckles to dive in deep learning. Before I did though, I thought I’d explain to my wife what I was going to do:

  1. Point the RPi at the birds
  2. Write a script to stream the camera’s output
  3. Find an machine learning model to take the video and detect the birds
  4. Send detected birds somewhere

“Why not use a motion sensor?”, my wife queried.

Maybe literally the first result on google, I found this article that walks you through in very clear steps how to setup a motion sensor using your camera on the Raspberry Pi.

I was getting emails and videos of birds in half an hour.

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