Inspiration -
Due to the recent increase in urbanization, negative impacts on the environment have also been on the rise. Actions such as deforestation, pollution, climate change, and water contamination have left many animal species affected. The WWF stated that humans are responsible for 99% of endangered and that the current extinction rate is 1000 to 10000 times higher than the natural rate. This shows the constant neglect of one of the closest neighbours to humanity and an integral part of our sensitive ecosystem. We wanted to create something that once again piqued the young generation's interest in nature. That's where Animatirx comes in. Animatrix is designed to be used by students and instructors to create a hands-on experience in learning about the vast diverse animal groups our world has to offer. Students can just take a picture of any animal and learn about it.
What it does -
Our web application Animatrix uses an AI which is hosted by a web application. The web application urges the user for an image of an animal and then outputs data connected to that animal such as its name, species, endowered status and some fascinating facts.
How we built it -
To build Animatirx our group was divided into two groups the frontend and the backend. The frontend was in charge of coming up with all the creative features that the user was going to be interacting with such as the webpage. This was done with HTML, styled with CSS and added features using JavaScript. The backend mainly used java while the AI runs on python. The basic procedure is that the user opens our webpage and uploads an image of an animal, the image is then passed to the AI which is trained and hosted in the backend. The AI will analyze the image and classify some data regarding the image and send it to the frontend which is then displayed to the user.
Challenges we ran into -
Some Challenges we ran into were during the API call when trying to integrate the backend and frontend using the backend's RestAPI. Testing these API calls meant that we needed to have all the technologies and aspects of our project run on our local computers, sometimes installing dependencies would give us errors. Some more challenges we came across were when making the webpage and trying to make it as user-friendly and visually appealing as possible. Since nobody in the group had ever worked on frontend development, we all were confused as to what a user might look for.
Accomplishments that we're proud of -
The accomplishments we are most proud of is having a final working product. The majority of the people in our group did not have prior professional experience regarding a hackathon. So to construct an idea from scratch into a fully working web application is definitely something we are all very proud of. Another thing we are proud of is getting through the challenges mentioned above. Regarding the frontend it was all made from scratch and having no prior experience. Some of the features of the frontend that we are especially proud of are the dynamic responses features. As you may notice the buttons have a fill feature when hovering over them. The webpage itself is made to fit any screen and even has a mobile response feature. As the window gets smaller the webpage will shift its contents yet still manage to look appealing to the eye.
What we learned -
Though the 36 hours of coding were stressful the lessons learned were plentiful. Through this project, we all got to learn the ins and outs of how an upcoming technology of AI functions, what it takes to get it up and running and what cases to consider when designing such strong software. We also got hands-on experience in taking a design from paper to canvas and making something tangible. We also learned a lot about how HTML and CSS work since this was software none of us had much prior experience in. Our team gained valuable experience in full-stack development and developing software as a part of a team.
What's next for Animatrix -
Currently, Animatrix is made to only work with images of animals. We are already looking into broadening the horizon for which images we can analyze. We are looking to make the AI smart enough to classify an animal based on footprints, feathers, nests/habitats, location, fecal droppings etc. We would also like to increase modes of inputs for the AI and not limit it to only visual cues but also audio cues. This will expose more opportunities for use. Looking a year into the future we would also like to start working on making Animatrix able to analyze environmental issues such as soil erosion, deforestation, ocean acidification, overfishing and more just by taking pictures of riverfronts, oceans and forests. Currently, the diagnosis of these sorts takes months if not years and requires many scientists to be present throughout the project term at the location in question so this type of technology could be quite revolutionizing.
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