What inspired us to create CHAKRA:
"What goes around, comes around".
CHAKRA (also means 'wheel' in sanskrit) and is also our way to denote 'Recycling'.
- We all are inspired by technology but we also know the ill-effects of it when not used properly. CHAKRA is our way to promote healthy habits like recycling and hence, to maintain proper balance.
- Technology + Business + Creating impact on this world and environment - This has been our mission since the beginning and the space apps challenge provided us with just the platform we needed to put our ideas into action.
- We as engineers know the power of a single line of code. CHAKRA will help us write those essential lines of codes to help people recycle their e-waste and hopefully, in the coming years, for the underprivileged to be able to use the fruits of our re-cycled technological devices!
Our approach and tools used in developing CHAKRA:
We all have been heavily dependent on electronics nowadays. The millennials, the Gen Z or infact the septuagenarians are seen being either hooked on to their mobile phones or any electronic appliance that reduces their day to day mechanical task. Thus, the problem of electronic waste is prominent and will be leading centuries to come. We all must take proactive steps to reduce, reuse and recycle the electronic wastes in order to save our environment from degradation. Going by that philosophy, we have made an application named Chakra. Here are the following technical specifications of our application:
- Platform : The application will be developed in Java Native platform on Android studio SDK version 28.0.0.
- Image recognition: To improve waste collection planning, individuals would photograph the waste item and upload the image to the server, where it would be recognized and classified automatically. The proposed system can be operated on a server or through a mobile app. A novel method of classification and identification using neural networks is proposed for image analysis: a deep learning convolutional neural network (CNN) was applied to classify the type of e-waste, and a faster region-based convolutional neural network (R-CNN) was used to detect the category and size of the waste equipment in the images. The recognition and classification accuracy of the selected e-waste categories ranged from 90 to 97%. After the size and category of the waste is automatically recognized and classified from the uploaded images, e-waste collection companies can prepare a collection plan by assigning a sufficient number of vehicles and payload capacity for a specific e-waste project.
- Apache web server.
- For buying and selling of second hand electronic appliances, the secured payment gateway will be used which will offer various supports like UPI payment, GPay, Amazon pay, Paytm wallet payment offers along with our own Chakra wallet wherein the redeemed points will be transferred and can be used for further shopping by the customers.
Problems:
- Advertising
- Brand establishments
- Creating awareness
- People not using recycled electronics much.
Achievements:
- Systematic approach developed.
- Developed a list of potential partner firms and potential e-recycle firms.
- Developed a strategy to compete with the already established competitors in the market who are fully functioning in this business.