You're literally describing how current automated doors work. That's because they can't infer what you actually want to.
Intuition pump: imagine the doors are actually manually operated by a set technician (like they are on Star Trek sets). Such a person can trivially tell, in split second, whether you're turning around to leave or just to check if someone is behind you, and open the door at the right time. They are inferring intent. This is what I'm saying transformer models are finally allowing us to implement in silico.
> Bug previously filed with cloud door vendor
Who is even talking about cloud here? Giving operational control over hardware to a third party located far away from deployment site is just monumentally stupid in nearly every case.
This is one of the top use cases for local models, because you need video feed processing with sub-second reaction time and real-time guarantees.
Also .15% of the time the door just randomly opens or stays shut with no rhyme or reason. Bug previously filed with cloud door vendor but told it's within door SLA and sent previously signed copy of agreement that "all neural nets are a black box and inherently probabilistic so errors may occur at any time and not a product defect"