Inspiration
A few years ago one of the team members learned about bird ringing in a summer camp. Bird ringing allows ornithologists to identify and track birds. The records are then uploaded to a database. Most studies regard the amount or variety of birds in a specific zone. We wanted to see what happened to a species as they migrated.
What it does
HiruSavior is a dataset visualisation for Hirundo Rustico, a migratory bird found all around the world. HiruSavior enables anyone to visualize the location changes of birds at their two main locations during the year. You can also visualize the relationship between global warming and the deviation of their migration. This opens the door to a new and revolutionary kind of bioindicators globally.
How we built it
We decided we would work in Python since we had in common some Python knowledge, for some as the only conding language.We first tried to obtain our data set directly from an API, but it proved to be too little documented. We had a huge database, so we had to choose wich data we could actually analyse. We decided to start working with only one species of migratory bird. The next step was making our downloaded .csv file usable. We prent a lot of time suck in this section because our file was really big and difficult to manage. After that we did some data visualisation with the plotly library.
Challenges we ran into
Initially we intended to use an API to retieve the data, due to the size of the database. However we were unable to find documentation that would allow us to build our requests or find useful keys. Another difficulty was figuring out how to format the database appropriately after downloading it as a .csv. This step was necessary for the visualisation of our data. Our hardware often wasn't as powerful as we would have wished, specially working with such a big dataset.
Accomplishments that we're proud of
• We all made our first step into coding autonomously. Two of us are in our first month in university, and one of us isn’t in the IT field.
• We stepped out of our comfort zone using tools no one on our team had used before, this includes APIs, .csv files and plotting libraries.
• Creating a tool that can change the world and save our planet.
What we learned
• Documentation isn’t always there, or if it is it may not be as good as you expect.
• Data can be heavy, good useful data doesn't have to be.
• Listen to your mentors, appreciate their time and their words.
• If your physical specs aren't cutting it, look for online resources.
• Data works in mysterious ways.
What's next for HiruSaviour
- Increase the number of species analysed.
- Improve predictions through Artificial Intelligence
- Track migration routes and their variations taking into account different clusters of individuals.
- Compare our wildlife databases with other environmental indicators.
- Save the planet.
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