ScanMart — Scan and Order
Have your parents or grandparents ever been annoyed that they couldn’t find what they wanted online? Or even if they did find the product, they couldn’t complete the order because of the tedious tasks involved. This is not uncommon.
About 87 percent of people aged 75 years and over have never been online. Seniors often struggle with reduced reactivity, making it harder to keep up with fast-paced technology. However, in the recent times, especially during a pandemic it is important to embrace technology.
The elderly may find it difficult to find and buy things online using websites and apps. Ordering anything online can be quite complicated for them involving many steps. In some cases, the websites aren’t user friendly and some may find it difficult to manually search the required product. Besides, there are many unwanted advertisements popping up which leads to a lot of confusion. Therefore, they usually depend on others to buy their essentials such as medicine, groceries, etc.
But this might not be the case anymore as we’ve got it covered!! Our project offers to help those who find it difficult to order online.
About the Project
Using this, the user can order any fruit by just taking its picture without the need to type and search for it.
The process involved here is simple. The user needs to take a picture of the product required using their phone. We’ve used Figma for designing the interface and OpenCV for image recognition. The application then finds the product on the linked third-party application. It automates the tasks like logging in, adding the product to the cart. It then directs the user to the payment gateway from where the user is left with minimal task of confirming the order and purchasing it.
We have trained the ML model using CNN (Convolutional Neural Network). Using this, it can take in an input image, assign importance to various aspects in the image to differentiate one from the other.
Then the user can complete the order after selecting the payment option. This not only saves time but is also very convenient for anybody.
Team Members: The members who worked on this Project are Deekshitha, Advaithh, Vidip and Yashaswini , supported and guided by our mentors Rohit Singh and Charvi.
GitHub Repo Link:
