Upon discussion, we learned that the majority of our team members are financially independent, and our busy lifestyles, catalyzed by school, work, and other factors, sometimes diverted our attention away from focusing on aspects which promote an eco-friendly lifestyle. Trips to school, electricity/water consumption and even our local grocery bills are all factors which can contribute to the detriment of the Earth’s state, that many youth may not even be aware of yet. While over consumption and global warming are factors which have been amplified in 2019 and continue posing a threat to the Earth’s future, we have a secret weapon- youth, the generation of the future, who are responsible for nurturing the Earth back to a more stable, less concerning condition. Consequently, youth must try to establish good environmental habits, but the transition from student to adult barely leaves time for deep contemplation about their consumption trends.

The TD API prompt captured the issue that we were trying to solve perfectly:

How might we best provide financial help needed by those transitioning from student-hood to adulthood?

So, we decided to design and develop grash (green + cash), an Android application which helps young adults keep the earth clean, while their bank accounts turn green.

What it does

The app is broken down into 3 distinct sections; “environment, home, and finances”, and incorporates a Microsoft Azure project, server side application, a client side application and the TD Da Vinci API.

Upon launching the application, the user is given the option to scan their receipt using their phone’s front camera. Upon scanning, the photo is sent to Microsoft’s Cognitive Services OCR, and Microsoft Azure parses the values on the receipt, extracting and comparing them to the "Legacy Release of the USDA National Nutrient Database for Standard Reference (SR-Legacy database)", which contains approximately 8000 of the most common foods in North America. Then, the fresh produce (fruits/vegetables) scanned on the receipt are classified as “off-season” (not available during these months) or “in-season” (available during these months), along with being locally-grown or foreign imports (in this case, in-season/off-season is neglected), and if an import, retrieves the distance between the country it’s imported from and Canada, by using the maps and geosphere libraries.

Then, the server-side code tallies an Eco-score: a point system which serves as a numerical indicator of the user’s eco-friendliness. Environmentally irresponsible factors such as purchasing off-season and foreign produce would subtract one point to the Eco-score, while using reusable bags and refillables would add points and result in a higher Eco-score.

Other factors parsed from the receipt which would decrease environmental friendliness of the user’s shopping trip, such as plastic bags and 6-packs, would also contribute to a lower Eco-score.

A counter would illustrate the user’s Eco-score in comparison to their friends’, who’s profiles would be fetched using Da Vinci. This enables the user to gauge whether they’re paying a lot more for utilities or for rent, which is sometimes a sensitive topic to ask friends about.

The second feature of the app is the ‘Finances’ section, which retrieves user’s reward transactions via the TD Da Vinci API. Using the transaction tagging, every transaction we did between the user’s chequing and saving account could be tallied. We tag these special savings the users have as rewards, both for them and the planet, as they saved money while contributing to a more eco-friendly environment.

In order to incentivise both the user and TD bank, grash has the option of transferring the sum of money saved by eco-friendly actions into an investing account. This benefits the user because the user would be sending money into a TD investing product that was determined to coincide with their goals and financial position.

How we built it

We incorporated a variety of APIs including TD Da Vinci, REStful, databases, and Android Studio to create the application. The Android application itself was built with Kotlin. The back end was written in Python, with the REStful API built with Flask to send data between the application and server.

Challenges we ran into

• On-boarding onto a new stack quickly • Integrating different parts of the project together (such as how to parse the receipt and send the information to Azure)

Accomplishments that we're proud of

We were proud of how quickly we were able to adapt to the environment.

What we learned

• Cognitive Services OCR • TD Da Vinci API

What's next for grash?

• On-boarding to personalize the tips received on the "environment" screen • Auto-investing • Ability to upload screenshots • More user input - confirmation of certain purchases and tailored tips

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