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Landing Page
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Buying Page
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Selling page
Inspiration
On way to this event, one of our teammates talked about the spare electronic waste accumulating at his home. As part of this discussion, our team also discussed how valuable metals such as gold, silver copper get wasted and get wasted and accumulate in nature. After learning about our problem statement, "managing waste in our city", our teams decided to specifically work on to tackle the problem of huge generation of E-waste and having no proper system to manage it. For this we created a Web application called "RunEWaste", which enables the user to list out there E-waste on our application at the same time another user can work with the working parts of it. In this was we are maximizing the utility of the generated E-waste before it is of no use at all.
What it does
Our Web application "RunEWaste", provides the user with Two interfaces,
1. The user can visit our model and list their spare electronic waste item on our website via the 7 easy steps process. Here, the user would first describe the working of their spare electronic waste item and then it will get validated through the ML model integrated.
2. The user can visit our website to scroll for buying the spare working parts of the electronic waste listed on our application.
How we built it
Our team have put the our heart and soul in building this application. Our whole web application is based on the MERN stack along with the integration of ML model. For the front end part, we used React js , for backend we used Nodejs and EXPRESS js. For database we used MongoDB. The backbone of this application is the database management done via MongoDB. We used MongoDB to generate User Profile, Categories of the product(Displayed on the Buy side of the model), User behaviour and Product details. Besides this we created a ML Model for validation of the product.
Challenges we ran into
The foremost challenge faced during building of this project is the integration of Machine Learning model with our MERN based Web application.
Accomplishments that we're proud of
Throughout making of this project we learned much more about our Tech stack which we used in the project
What we learned
We learned more about our dependancied like pickle, ML etc.
What's next for RunEWaste
For Future we are planning to make a reward system which will reward users who list their items on our web application so that it would keep motivating them to manage the E-waste on our model.
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