Inspiration

To tackle the issue of compromising on a place for friends to grab a meal, we came up with the following solution,MakanWhere. We considered the distances of users, their preferences in cuisines and their budget to quickly generate nearby food locations for them to choose from. Our guiding principle was to make the bot as convenient and as usable as possible. We drew inspiration from the Bus Uncle Bot. It is a simple bot that tells you the bus timings given a bus stop location. However, its easy to use and satisfies a real need. This is what we tried to capture when making MakanWhere.

What it does

MakanWhere recommends food places based on users' preferences such as budget, location and cuisine. Simply add the @Makan_Where_bot to your telegram group to get started!

How we built it

We used the pyTelegramBot library to build our telegram bot in python. We also made use of the Google Maps API to handle the locations of users and find nearby food places.

Challenges we ran into

Due to lack of documentation within the pyTelegramBot library and the fact that this was the first time we used this library, development time was much longer than expected. We also encountered minor issues when dealing with many users concurrently. However, our dedication to overcome these setbacks enabled us to think out of the box and resolve these issues.

Accomplishments that we're proud of

We created a user-centric telegram bot that solves a real need. This is something that we would see ourselves using. (While testing out this bot, we also found some pretty good food places near our homes that we didn't know about)

What we learned

This is the first time that we tried making telegram bots using the python library. We also learned how to leverage on Google's services to enhance the functionality of our bot.

What's next for MakanWhere

Allow users to enter more preferences such as

  1. Mode of transport (car / public transport / walking)
  2. Incorporate machine learning models find a central cluster of restaurants instead of just calculating the middle point
  3. Calculate time to leave given meeting time for each user based on their mode of transport
  4. Highlight food places with vouchers and discounts nearby
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