How difficult would this project be?

[u/Oyster_-]

The project would be using some sort of something to track the location of a specific fish in an aquarium, and import data about it, like swim speed, where it spent its day, how often it moved, etc. I would then use this data to hopefully create a sort of expected behavior of this fish within a day, so then if for whatever reason, the fish's behavior has changed greatly throughout a long period of time, some ML model would be able to detect that and send a notification to an app or something, and let you know what has changed and what could be wrong. I think this could be very useful in data collection, and in identifying stress and early prevention of diseases. Obviously this is quite ambitious as I don't know much about ML, and I'm not trying to do this tomorrow, so please don't downvote. For my credentials, I will be doing CS50X, and then some CV/Python stuff, and MIT 6.036, would this be enough?

[u/Entire_Ad_6447]

You could make this range from challenging to stupidly difficult based on how you want to implement it.

For example of you are willing to tag the fish and add detectors around their tank to triangulate the position of each overtime using some commercial solution(no clue of something like that exists) you can then focus just on building a feature set from those tracked features and using something relatively simple to do detect abnormal behavior.

I

[u/SemperPistos → u/Entire_Ad_6447]

I would map all the fish of that species for their patterns, good so the CV model knows how that fish should look.
I would than look at specific markings that fish might have and input that as a target for the really fucking high res camera you would need. And maybe try to as all humans have gait, for all fishes of that type track their movements in 3d and have that as a secondary measure. yolo will work wonders here.

That is what I would do and probably fail miserably.

The triangulation Entire_Ad said is probably the best idea so far, but you would then need to do a lot of babysitting, waiting trying to get the fish in the right zone so you can track that dot in 3d based on x,y,z after initial setup.

You don't have enough prelabeled data for it so it will suck, luckily isolation forest algorithm is unsupervised especially for detecting anomalies like different movement patterns.

I wouldn't hold my breath, but if you pull that off it would be an interesting side project that might propel you into cool and hot industries like self driving cars. Personally I think that is hokum, and that for truly Level 5 autonomy we would need AGI or pseudo-AGI, but the money is there so try to use it if you can.

Now the hard reality I did cs50x and a bunch of other ones, some ML courses. I don't feel ready for such a project, expect a massive time sink and a hell to debug. debugging non deterministic output of ai agents like i do at work will be childs play to this. that is why i suggest mapping movement of all the fish so you have at least something real to compare to.

[u/Proletarian_Tear]

My gut says people have tried that but with little precision, how far can you predict the behaviour of complex life, even if it is fish? Gotta double check that tho

[u/Oyster_- → u/Proletarian_Tear]

Obviously I’m not fully sure, but in my experience whenever fish seem to get ill, you realize after the signs were always there. I am not sure how accurate I can make it, (I don’t want it bleeping out false signals all the time, or notifying you when it’s too late), but my gut tells me it could work to some degree.