Jarvis

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  Customer hearing the dessert options (In restaurant, Jarvis would say this out on a google home. This is just a simulator)

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  Customer options for appetizers being adaptively narrowed down

Inspiration

One of my family member is visually impaired. She told me about the difficulties she faces in daily life of which one was the easily solvable problem of eating out at restaurants. We wanted to help people over the world like her who don't like bothering their friends to read out each item in the menu or depend on the server's suggestions only. Using Jarvis, they can now have a wholesome interaction with the server of the future.

What it does

A user can interact with Jarvis and Jarvis will intelligently guide them through the restaurant's menu, suggesting items on the basis of the user's preference, ultimately helping them decide what they want to order when the waiter stops by!

How we built it

Jarvis can be adopted to any restaurant. All it needs is a database of categorized menu items which we have implemented using FireStore. We have made Jarvis's voice agent aspect using Google's DialogFlow and all the logic and handling code is written in Node.js and hosted on the Google Cloud Platform.

Challenges we ran into

Trying to incorporate firestore db into our voice agent

Accomplishments that we're proud of

Incorporating Firestore into our App

What we learned

DialogFlow Firebase FireStore

What's next for Jarvis

Populating our Firestore using a web scraping app that parses Zomato menus and automatically fills in the Firestore for a specifc restaurant Create app endpoint to receive orders placed by clients

Built With

• dialogflow
• firebase
• firestore
• google-cloud
• node.js