## **Problem**

* Less than a third of Canada’s fish populations, 29.4 per cent, can confidently be considered healthy and 17 per cent are in the critical zone, where conservation actions are crucial.
* A fishery audit conducted by Oceana Canada, reported that just 30.4 per cent of fisheries in Canada are considered “healthy” and nearly 20 per cent of stocks are “critically depleted.”

### **Lack of monitoring**

"However, short term economics versus long term population monitoring and rebuilding has always been a problem in fisheries decision making. This makes it difficult to manage dealing with major issues, such as species decline, right away." - Marine conservation coordinator, Susanna Fuller

"sharing observations of fish catches via phone apps, or following guidelines to prevent transfer of invasive species by boats, all contribute to helping freshwater fish populations" - The globe and mail

## **Our solution; Aquatrack**

aggregates a bunch of datasets from open canadian portal into a public dashboard!

slide link for more info: <https://www.canva.com/design/DAFCEO85hI0/c02cZwk92ByDkxMW98Iljw/view?utm_content=DAFCEO85hI0&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton>

The REPO github link: <https://github.com/HikaruSadashi/Aquatrack>

The datasets used:
1) <https://open.canada.ca/data/en/dataset/c9d45753-5820-4fa2-a1d1-55e3bf8e68f3/resource/7340c4ad-b909-4658-bbf3-165a612472de>

2)
<https://open.canada.ca/data/en/dataset/aca81811-4b08-4382-9af7-204e0b9d2448>
## Inspiration Personal Experience

Save the global fish stocks from destruction by balancing hunger with overfishing!

## What it does

This is a Webgame that

## How we built it

Javascript, html, css, Google API

## Challenges we ran into

API and AI

## Accomplishments that we're proud of

AI for fish tracking

## What we learned

Programming is fun!!!!!

## What's next for Fish Simulator

Increase modern issues and their affects, and make sure the fish don't go on the end
## Inspiration

Recognizing the disastrous effects of the auto industry on the environment, our team wanted to find a way to help the average consumer mitigate the effects of automobiles on global climate change. We felt that there was an untapped potential to create a tool that helps people visualize cars' eco-friendliness, and also helps them pick a vehicle that is right for them.

## What it does

CarChart is an eco-focused consumer tool which is designed to allow a consumer to make an informed decision when it comes to purchasing a car. However, this tool is also designed to measure the environmental impact that a consumer would incur as a result of purchasing a vehicle. With this tool, a customer can make an auto purhcase that both works for them, and the environment. This tool allows you to search by any combination of ranges including Year, Price, Seats, Engine Power, CO2 Emissions, Body type of the car, and fuel type of the car. In addition to this, it provides a nice visualization so that the consumer can compare the pros and cons of two different variables on a graph.

## How we built it

We started out by webscraping to gather and sanitize all of the datapoints needed for our visualization. This scraping was done in Python and we stored our data in a Google Cloud-hosted MySQL database. Our web app is built on the Django web framework, with Javascript and P5.js (along with CSS) powering the graphics. The Django site is also hosted in Google Cloud.

## Challenges we ran into

Collectively, the team ran into many problems throughout the weekend. Finding and scraping data proved to be much more difficult than expected since we could not find an appropriate API for our needs, and it took an extremely long time to correctly sanitize and save all of the data in our database, which also led to problems along the way.
Another large issue that we ran into was getting our App Engine to talk with our own database. Unfortunately, since our database requires a white-listed IP, and we were using Google's App Engine (which does not allow static IPs), we spent a lot of time with the Google Cloud engineers debugging our code.
The last challenge that we ran into was getting our front-end to play nicely with our backend code

## Accomplishments that we're proud of

We're proud of the fact that we were able to host a comprehensive database on the Google Cloud platform, in spite of the fact that no one in our group had Google Cloud experience. We are also proud of the fact that we were able to accomplish 90+% the goal we set out to do without the use of any APIs.

## What We learned

Our collaboration on this project necessitated a comprehensive review of git and the shared pain of having to integrate many moving parts into the same project. We learned how to utilize Google's App Engine and utilize Google's MySQL server.

## What's next for CarChart

We would like to expand the front-end to have even more functionality
Some of the features that we would like to include would be:

* Letting users pick lists of cars that they are interested and compare
* Displaying each datapoint with an image of the car
* Adding even more dimensions that the user is allowed to search by

## Check the Project out here!!

<https://pennapps-xx-252216.appspot.com/>