PikoMenu

home page of pikomenu
sample targeted review on yelp
fetch data from yelp
sample results for searching for food
sample results for restaurant results

Inspiration

Have you ever felt confused by incredibly simplistic menus with the most verbose, complex food names? In a world surrounded by technology and advancements in the social web of humans, we lack the capability of seeing what we’re about to eat.

PikoMenu is the prototype of taking crowdsourced images via the Yelp API and intuitively matches them to the food on menus to provide a cohesive, one-of-a-kind experience when eating out. No longer must you be confused by different languages or vague explanations. See what you eat and eat what you see. Never be confused again!

Did somebody say… food?

What it does

PikoMenu fetches data of restaurants nearby you and gives users the option to select the restaurant they’d like to view. The service then pings the Zagoto server to match restaurants with menu data. By creating a correlation between Yelp’s picture reviews and the menu items in real time users will be able to quickly determine their best options for that restaurant.

How we built it

We built our own JQuery library of functions that utilized the Yelp and Zagoto database. We then had to cross-reference both sets of data to create a comprehensive restaurant menu for users to be able to access. We used Bootstrap for the front end design and Adobe Illustrator for the logo design.

Challenges we ran into

Our initial ideal was to use React.js, however the learning curve was too high for such a comprehensive library with the lack of javascript expertise on the team. We mitigated for our lack of knowledge by opting to use JQuery and had to exchange productivity. We also struggled with dynamic animations for the landing page as an attraction point. The largest issue we ran into was a difficulty of reaching the Yelp API. The system of retrieving and recording the Oauth tokens were lacking in proper documentation and left much to the imagination of the developer.

Accomplishments that we're proud of

Two team members with limited experience in front-end development picked up the utilized languages and tools at an exponential rate to be able to design animations for the front page. We were able to implement a unique idea to a decisively large pain point in the community, enriching the experience of already available technologies.

What we learned

The biggest lesson of this hackathon was a lesson the great Muhammad Ali taught the world: “Float like a butterfly, sting like a bee.” Much like the butterfly, we had to deal with constant changes in our game plan due to changing environments, equipment, and team availability. We overcame these struggles by striking like a bee when it mattered and crunching down to build a strong end-to-end concept.

What's next for PikoMenu

PikoMenu is not limited by the current functionality. We hope to be able to expand into the Azure Machine Learning Studio to create food profiles for our members. These food profiles could grow to eventually order food intuitively for users based on their past preferences. We also hope to expand our application to be an end-to-end service for restaurants as a comprehensive photo menu partner. Finally, PikoMenu is about the experience of the user. We hope to be able to grow into a useful and well-used app to improve the lives of members in our community in any way we can.