Create your own smart baby monitor with a RaspberryPi and TensorFlow

So, don't get me wrong. This is a fun project and a neat little device. I don't mean to take away from it in any way.

However it is really important to consider why baby monitors are so primitive: because the cost of a false negative is huge. I didn't see any mention of this in the author's experiments (only a '>98% accuracy' note). So let's talk about this a little bit: is "accuracy" what we want? Probably not---I don't care if I get accidentally notified, but I care very much if I don't get notified when the baby is crying. So you want to weight your classifier's predictions heavily against false negatives (at the price of false positives). It would be good to make an ROC curve to characterize this behavior. More importantly though, any predictive model assumes a stationary distribution; i.e., training conditions accurately reflect test conditions. But will they in real life? What about when your neighbor's house is under construction? Can interference from chainsaws cause the model to fail to detect the baby crying? What about the dude down the street with his super loud motorcycle? What happens then? I bet the training set doesn't have situations like this.

I really, really don't want to come off like a wet blanket here. But I feel obligated to, because this is a model that directly impacts the welfare of a human, and so we should at least talk about or discuss potential drawbacks. (Again, cool weekend project, just, we need to be clear about the implications of outsourcing the decision of whether the baby is crying to a black-box model where we can't interpret what it's doing.)

Was going to come here to say something very similar. I'm no luddite, but some things really shouldn't be left to tech like this...

"Lavish attention on me and entertain me."

― Maggie Simpson via the baby translator

https://simpsonswiki.com/wiki/Baby_translator

That being said, every parent knows the "he/she has never cried like this" moment where your blood freezes and you rush to the child's bed. Seems hard to add this to the model in a reliable manner.

But the tech exists. It's not like we're using tin cans and string and trying to replace that with a gizmo; we have the gizmo, and now we're trying to make an open-source version of it. While the goal is admirable there's no real benefit from using a less-tested Raspberry Pi project. There are less risky ways to learn the same lessons - a video walky-talky maybe.

Forgive me for bringing it up, but this is also the reason why smart gun technology is a complete dead end.