Inspiration

During the pandemic era, everyone is at courtesy of social help and this requires a large number of contributions from people. But doing this physically is not feasible. Working in CS requires being able to work efficiently in teams. But many students just slack off as they are unable to form/find a team. There’s also lack of social awareness towards nature and how important contributions are, may those be for social good or personal development for a student. With Alute, we aim at tackling both of these problems with a single solution.

What it does

On Alute, Learn and Contribute, a user can create projects, join teams for projects created by other users after reading about them, and work towards project completion to earn credits. These credits can be used to contribute to the nature and society by exchanging them to plant trees, donate or for charity, and such purposes. By spending their credits for such noble causes, the users earn a customized platform currency that would be used to award them badges. Our focus is that we create a place where young minds don't just get a chance to develop their coding skills, but also contribute to the society and thus indulge in a healthy competition for badges.

Features

  1. Free of cost for all users. Once, signed up, users can go to dashboard for details on how exactly Alute works.
  2. An FAQ chatbot to help them with any queries about the platform.
  3. Joining a project or a team, after analyzing it properly.
  4. Creating a project and providing opportunity to other users to join.
  5. Credits: after successful completion of project, credits will be awarded by admins. Can be used to contribute in numerous ways with chance to avail a gift card as well.
  6. Alutoze: our very own virtual currency. Will determine the badge earned and help strengthen the profile. These can be earned by spending credits.
  7. GitHub account linking to ensure legitimacy of project completion. Same will be scrutinised before releasing credits.
  8. Project history tracking. comes in handy before accepting a project collaboration request.
  9. Pro and Premium accounts (yet to be introduced)

How we built it

  1. The first step was ideating and thinking of various features and design that we could incorporate.
  2. Next, we prepared a wireframe of the application and split the work among ourselves and set specific deadlines for specific tasks.
  3. So, simultaneously the implementation of Front-end, Back-end and ML was in top gear.
  4. Next, we had to integrate front end with backend and then the integrated web app with ML model to complete our dream project and voila!

Challenges we ran into

  1. ideation and feature deciding took a lot of time.
  2. Designing a lot of webpages and implementing it within such short duration was a major challenge in itself.
  3. Integrating frontend and backend with proper routes and requests. We ran into lot of bugs and server was crashing very frequently. Debugging the code and making server run smoothly was another challenge we faced.
  4. With respect to chatbot, we had to generate our own custom data, which is a tedious task and again consumed huge amount of time.
  5. Once, that was done, increasing the accuracy and choosing the most efficient and best bit model was another challenge that we faced.
  6. Integrating the python code for ML with backend in JS was our ultimatum.
  7. Deploying was also a challenge in itself, and we found a way, but unfortunately, the max slug size for Heroku is 500Mb and our was over 700Mb. Hence, we had to remove chatbot functionality from the hosted application. But the entire source code can be found on GitHub repository

Accomplishments that we're proud of

We faced a lot of challenges, but also learned a lot of things while trying to overcome them and hence we are satisfied with out work! We are also proud of making a fully function web app within such short period of time, with all that hard work and sleepless nights!

What we learned

We learned, collaboration, working in teams, trusting each other with work, how to integrate backend with ML models, some new frontend, backend and ML concepts too!

What's next for ALUTE

  1. Better and more efficient platform
  2. App for the same for easier track of features
  3. Better resources, collaborations and connections
  4. Additional features such as Plagiarism Checker, Analysis of level of projects, all powered by AI. Helping maximum number of users and society and conserving the nature is what we aspire. We also dream that, one day, Alute will be the primary go to platform for all projects related work and even recruitments for top MNCs!

Detailed view can be found here

GitHub Repository can be found here

Demo Video can be found here

Hosted website can be found here

Note: The Entire demonstration could not be shown in the demo video due to time constraint, for Eg. Admin Portal.

To check the same login with srishti@gmail.com password: 1234 on the hosted application on heroku and visit "https://alute.herokuapp.com/admin"

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