Inspiration

We were inspired by how Pokémon Go was able to get young people interacting with their surroundings and local environment, and thought that this same interest could be captured or utilised to educate and enable young people, particularly children, to interact with wildlife around them.

What it does

It enables the user to keep track of the various animals found around them, and rewards them with stickers, fun facts and points for finding both new and existing animals. It provides suggestions for animals the user may find in the area based on their location, and keeps a track of all finds. Especially for kids unable to identify the animal by name, they can go through the quiz to identify the animal and add it to their collection, thereby also learning the scientific method of classification of animals.

How we built it

We built it using the library Pygame using the programming language Python. We built it on our laptops, although we are intending to implement it on mobiles and tablet devices.

Challenges we ran into

The map-box API to enable tracking of the current location was difficult to integrate into Python, however would be much simpler once the app is translated into mobile developing languages such as Swift, Java, etc.

The camera utilised OpenCV, which we were able to function as an individual component, but had trouble integrating it into the PyGame system.

Accomplishments that we're proud of

We were able to build a working application in High Fidelity that could definitely be useful in the education of children learning about the world around them and improving their knowledge and also physical activity through animal spotting.

What we learned

Teamwork is very essential while working on a project of this calibre and in such a timeframe. It was necessary to communicate our progress and collaborate to help fix bugs and build a successful product.

What's next for Animal Adventures

We would like to use OpenCV to enable machine learning so that photos of any animals caught can both be more accurately guessed by the device as, for instance, a pigeon, but also enable a greater accuracy with the sorts of photos of each animal that are photographed.

We would like to use data on the backend to enable conservationists to utilise the information from photographs taken of animals in specific locations to determine species numbers and aid in tracking and conservation efforts.

We would like the location function to work in showing previously found animals' locations for the user to know where they may be able to find animals again and track their progress. As well as providing a warning if there are dangerous animals in the area and relevant safety information.

There could also be further gamification in the app further incentivising children to engage with the app, this could be in the form of minigames (similar to those in the app 'dumb ways to die').

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