Great Catch!

A social fishing phone/mobile app that tracks fishing activity for science.

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Inspiration

We attempted to mainly tackle problem set 1, Billfish, but came up with an idea that can cover problems in multiple problem sets in this competition. Previous entries such as Fish-o-tron focused on technical ability to measure fish with a smart phone. Our Project focuses on social appeal and an algorithm for identifying specific fish species.

What it does

Phone app asks small fishery or recreational user to set their destination of where they are going to fish. The location is used to download a data set from the server of fish species known to be in that area and of concern to scientists. User is reminded to print out a fiduciary image to help the phone determine fish size. When fish is caught, a picture is taken by the user with fiduciary in sight. App then chooses from the data set which species fit the image best using our grayscale algorithm. User can alter sorting options if the list of possible matches is too long and they know something about the fish. Keep/Throw is part of the submission and will come with emojis to indicate when keeping that species is ok. Immediate gratification from the gamification of the app congratulating the user for their catch. Badges, goals, stats, achievements quests, etc. Sharing location publicly with other users will be optional, but the scientists on the server side will still get time stamp and gps data. When in range of a signal, the app uploads submissions made to the server and posts them to the website where other users can crowd source to verify correct species identification. Events, quests, achievements and other game features can be used to campaign for increased awareness and social efforts to protect fish populations and other ecological concerns.

How we built it

Python script to demonstrate that the algorithm can sort fish images using our fingerprint method

Challenges we ran into

Determining a simple method for identifying fish species with an algorithm. Not enough time to build a complete model. Summarizing our concept in 5 minutes

Accomplishments that we're proud of

Grayscale intensity mean plots showed more detail about a fish species with less overall size of information needed. Presentation and demonstration deliver the realistic possibility of making this app.

What we learned

There is an interest and a need to obtain and share data of fishing activity both for social interaction and for the ability for scientists to monitor fisher activity.

What's next for Great Catch!

Despite not getting 1st place we plan to continue building the app and will see if we can manage to build enough of a prototype to get the financial backing to complete it.

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