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I actually work in this field and it's a lot more complicated than it sounds. When you're training AI to recognize products in a store, you have a set list of products it needs to be trained on. A person might go to many different stores which increases the possible variation of products exponentially. Amazon's model is also much more complex than just cameras, involving weight sensors in shelving, pressure detection, facial recognition. A store where everything is laid out in predictable, well lit, organized rows is already a nightmare. A fridge, even if it's way smaller, is way, way less predictable

A typical Amazon store that I've been to is around 12,000—16,000 feet. A refrigerator is approx 20-25 cubic feet of real estate.

Miniaturization of any system is always going to be a massive hurdle.

Amazon uses biometric recognition to determine if a person has picked up something, RFID tags, Weight Sensors, cameras, Laser gates and probably some other things they aren't telling us about.

They also know a specific list of the items in the store and have 3d models for where each item is. nothing unexpected.

For the fridge to work it would need to know every product ever made and have accurate and reliable scans of the existing product. Sure it might be able to find SOME of the same type of item but it will only work once it can find the EXACT item that I want everytime.

Good luck finding my favorite brand of Guachujung that can't be purchased online and is only available from a shady mom and pop grocery in Asia town.

LASTLY... what's a camera going to do with this:

Good luck guessing how much milk is still left in the non transparent package

Given you re-design it from the ground up, that'll work 🤷