As someone who has to deal with a lot of boilerplate construction permits all day, this is actually something that AI could be useful for.
I’m creating the permits, so I have total access to the spatial design databases for internal QA, but permit reviewers with the city/county usually only receive a PDF or some other document format.
These drawings frequently have thousands of dimensions each, and tallying them up by hand can be a bear. Training a hyper specific model to look at an image of a permit page and highlight areas where possible dimensional conflicts could be or find other commonly overlooked mistakes would be really helpful.
They absolutely just mean slapping a screenshot into GPT3o and calling it a day though…
That sounds more like a scenario that would benefit from electronic data integration, not heuristics-based machine learning. There’s way too much stuff that still uses formats designed for human consumption.
Totally agree, migrating to using spatial databases and accepting permits in forms other than paper/PDF would make everyone’s lives so much easier.
The industry still isn’t very caught on to geospatial stuff at that scale though. Most draftsman work is still just draftsman work, a very manual process. Having a way to help validate and pre-screen those permits would still be helpful while people start migrating to better systems over the next decade or so.