Our Inspiration was a simple problem that affected all of us whether we searched up a show or gaming console. Sometimes even a whisper of a product seemed to trigger endless targeted ads, from Facebook, YouTube, and even Edmodo. We wanted to use new technologies such as a decentralized net to provide users with a way to shop smart without selling their digital personas to big tech companies.
What it does
Our program works with Google Keep to read through a wishlist of items that users want to buy. It then automatically searches for the cheapest prices on all popular platforms from Amazon to Alibaba to Walmart. It then uploads links to these sites on a Blockstack supported shopping list. User's interests and wishlists are protected and private while universally available. This is an initial step in the direction of providing users more privacy on their online shopping habits.
How I built it
I built it using Blockstack technology and the PathUI studio. We coded most of the website in java script. It was styled using CSS. The backend for the product is also powered by Gaea, which is more secure.
Challenges I ran into
We ran into a number of challenges. The most significant was the time crunch, forcing us to learn new technologies. We had a lot of trouble installing json and getting the node to play well with BlockStack's encryption keys. We were eventually able to debug problems. Another issue was also integrating our work across different OS. We were transferring work between a UI platform, Linux, Windows, and Mac. However, we persevered through issues, and by meticulous organization, we were able to integrate all the moving parts into one.
Accomplishments that I'm proud of
We are really proud of being able to implement a complex application that acts as a simple starting solution to a very big problem currently. Both Blockchain and Path UI were truly foreign subjects to us until the events of the Hackathon. It was really a struggle to go through and understand all the documentation, but all the hard work really paid off. Finally we are proud of our team's communication throughout the project. From taking shifts to working through problems together, and taking care of each other, this has truly been one of the best experiences working on a team that any of us have had.
What I learned
What's next for SmartShop
The next step for SmartShop is to become more user-friendly and to use an ML model we started creating to determine the cheapest prices for any product including shipping, taxes, discounts, coupons etc. We would also like to introduce a social aspect to the app that encourages more members to try Blockstack applications and help advance the future of the Internet.