ONE GO!

Inspiration

Our team attempts to explore innovative applications in a world that is significantly impacted by COVID-19. The food hospitality industry, which is traditionally dominated by dine-in services, witnesses an enormous increase in demands for contact-free services such as delivery and curbside pickup. While delivery is supported by a wide range of awesome apps such as DoorDash and UberEats, there haven't been a lot of applications that are specifically curtailed to curbside pickup, which offers a more flexible option of dining at a much affordable cost. This shortage inspires our idea to use NCR BSP APIs to create a curbside pick-up optimization platform, as our project for the HackGT 8 challenge.

What it does

One day, you have an irrational thirst for sushi :sushi: and boba tea :bubble_tea:. However, you're not sure which sushi restaurant and which boba tea shop you should drop by so that you can achieve both of the following objectives in a one single pickup route :car::

travelling at the Shortest Distance
Getting the Best food quality of both restaurants together

This is precisely where our web application comes in. Our “bundling” option allows customers to order from multiple restaurants and pick up their orders in a single trip without swiping through different apps. Given a list of multiple keywords, we conduct fuzzy searches on each one of them and create a set of combinations of eateries (and groceries, by the next extension) between each search. Each combination is treated as one item, and for each combination, our ranking algorithm computes a combined score from 1) the weighted average rating of all restaurants in this combination, and 2) the total distance of the shortest route that covers all restaurants in this combination.

How we built it

We have built the frontend with Javascript and React, and the backend with Python that is also used to connect the API from NCR and Google Map.

Challenges we ran into

The API from NCR has a unique syntax. We took quite a long time to familiarise ourselves with the usage of the API and fix the errors arising in using the the API.

Accomplishments that we're proud of

We have built a robust web application that can perform optimisation of restaurant bundles based on multiple factors, known as travelling distance and average reviews. The user interface is user-friendly and clean.

What we learned

It is the first time experience for most of our teammates to apply API in a real application. We have also learnt to work under the pressure to create a functional web applications by connecting the frontend and backend infrastructure.

What's next for ONE GO!

NCR BSP API Challenge: One Go! We are exploring options to include more methods of MENU API from NCR, which are not available for this Hackathon this now. With this API in place, we have a more sophisticated platform that can help the customers to order the food on the fly in ONE GO!