From my experience any rules based approach in linguistics may solve the problem at first but it won't scale for too long (it has been tried before, most of old NLP was very rules based I would say) due to many intricacies of languages, corner cases and non-obvious exceptions. It could work — and it fact it does — for simple scenarios, but these are not very real world ones IMHO. I believe a neural model of such cases, over time, will yield better results. I am very skeptical these days about doing computer linguistics without considering some level of AI (so to speak).
I'm sure air conditioners in US banks or public offices consume more energy than Bitcoin mining worldwide. They never turn off computers at night, insurance companies require to leave lights on at night, each office has a few TVs with chomecast showing pictures of nature (irony ha!) all day and night long... but it's BTC mining they're fighting with.
To me color knowledge is akin to other cultural backgrounds one (who works in any slightly artistic environment such as UI/UX) must have a priori, not a posteriori of the work. It doesn't add up to your TODO list, that's what I am saying.
PS: image optimization should be done automatically IMHO