Thank you. I could be persuaded to change the title, though I don’t think I have been. (You are perhaps not trying to, but I’ll record my reasoning anyway.)

Re: nobody is motivated to do this. True, and doesn’t contradict the title or content. Anybody could drive out and start toppling power poles and poisoning the water supply, fortunately most people are mostly good.

Re: some houses are well insulated. Congrats on your nice home! Many dream of having their own space someday. I think the most interesting case is in an apartment/condo/high density complex. In this setting, you have:

• the layout of the entire building, including other rooms. (modulo furniture and dustables; the walls are public.)
• many routers all over the building, overlapping and generally at different frequencies. When I AirBnB, I often see dozens of different networks from my bedroom. Note that for this style of attack, you don’t need to connect to anything.
• thin walls between units (often cheap).
• some incentive towards snooping. Who stole your packages? Which neighbor keeps letting the dog poop at your window?

Re: training required and the field of view This I find most compelling. I am interested in how much legitimate use is required; can we simply make login attempts? Or does it take somebody logged in? It’s hard for me to tell how customized the model must be (this is a setting where data is reasonably easy to generate in a lot of settings; perhaps enough so that, given a model slightly larger, we get something general?).

The original title was substantially less clickbait; I amped it up in the hopes of a reply like yours.

If you have a moment more to enlighten me, I think you’re claiming:

1. This technique is location and person specific; the models don’t generalize if you move the router or change the people (and retrain on less data)?
2. This method doesn’t determine where folks are (even when used with multiple routers) to any useful precision? (Forget who, you can guess whose in your neighbors house)
3. This method is nowhere near getting plausible pose data?

My (also not that deep) understanding is that this took a technique that was very walk dependent, and made it robust to different walks? I suspect you’d also need to vary what and where the conductive element is, I would think. Otherwise you’re just extremely conspicuous (for being an outlier) on every readout. It’s like adding an RFID tag to yourself.

the wonder is that folks walked in different ways, and were still identified correctly. Not walking, you might be mistaken for furniture tho.

In public spaces, this is already happening with CTV from nearby stores and such no?

(I admit, I liked the cloud crowd better.)