Conflicts are bound to happen between roommates. However, the risk of conflicts breaking out could be minimized if people who share similar interests are being placed together instead of people who are at loggerheads being placed together. Furthermore, placing like-minded people together also encourages the residents of staying in the campus to be more helpful and to cultivate a habit of helping one another in need. People tend to gravitate more towards helping those they share similar interests / same course with, and placing them together would allow them to help out each other with their school work as well. However, doing a survey for every single person applying to stay in the residences in the campus could be a tough task to get a human to do. Therefore, creating a Telegram bot with multiple choice answers and the potential ability to save the answers to a database would make it much easier on whoever is doing the job. Furthermore, algorithms would do a better job than humans at such mundane and repetitive jobs, especially if the algorithm is a strong and accurate one.

What it does

The bot takes in simple information that we thought were crucial in helping decide which people are more compatible to live with each other in the hostels. The information we collect are things like the course they are taking, their genders, their sleeping hours and their socialization preferences. These factors can be important in deciding living arrangements, as it'll ensure that like-minded people / people who are studying the same course are able to hopefully live near each other and can work together on their school work / socialize together.

How we built it

We used the Python Telegram Bot library to build the bot.

Challenges we ran into

It was the first hackathon for all four of us in the team. Although 2 of the team members were NUS students, none of them have been to a hackathon before. Furthermore, the other two of us in the group were secondary school students. Therefore, our knowledge of the languages / frameworks / libraries that we were going to use were not as strong as the other groups. The four of us weren't familiar with what we were even doing to begin with, therefore had to read a lot of documentation, which we found complicated and time-consuming. We were also not familiar with working with each other, and had to get used to each other's working style fast. The lack of ideas also hamstrung our team quite a fair bit at the start, while technical issues that we ran into around mid-afternoon of the first day didn't do us much favours as well.

Accomplishments that we're proud of

We built a fully-functional Telegram bot that allows easy data collection to see of people are compatible as roommates. Those data could then be take into consideration when deciding roommates and living partners.

What we learned

First and foremost, we learnt about how to use the libraries and the different syntaxes. We also learnt a lot more about Python by exposing ourselves to a new library. Soft skills were also a point of learning for the four of us, as it was the first time any of us worked with someone with such a big age gap compared to us.

What's next for FindMyRoomie

We hope that it will end up widely used in universities and colleges with dorms as an easy way for dorms to be assigned. This will hopefully also prevent less-compatible dorm mates to be placed together and reduces the risk of friction between the students living in the campus residences. We also potentially hope to include a system where we could improve upon the bot by providing back end storage services.

Built With

  • python
  • python-telegram-bot
  • telegram-bot-api
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