Come along with us to participate in a fun filled hackathon that tackles online shopping in a new and creative way!
The problem revolves around recommending and categorizing optimal garments based on user input as well as popular trends. It involves the detection of the clothing articles in your bag through which one will have to pay online before they can exit the store with their purchase. The application of neural networks along with clustering algorithms make this model alluring.
Creating classes based on popular trends with the help of clustering algorithms. Recommending based on filtering and personal preferences.
Locating the outfit with the help of RFID tracker on the tag of the clothing article. Once exited through the detector, the RFID chips get tracked that will finalise the items in cart for the total bill.
The exit won’t be permitted till you pay the bill online or cancel the cart.
Simultaneous application of regression and clustering techniques Say bye to standing in lines at your favourite’s store billing counter. The long search would be shortened with the help of RFID trackers on the clothing. The counters of every apparel would be visible on the online store There won’t be any staff at the store to interrupt the introverts. Payment option on online app would be available right after crossing the detector. The application creates outfits for everyone, and recommends accordingly. Along with the comfort of an online store, the real life store helps you try on your favourite articles.
In a retail store, an RFID tag originally came in the form of a rigid plastic pin that was attached to a product. Now, they are as small metal prints on fabric tags, having information about the garment's size. The device contains a tracking number associated with that particular model, color, size. With the widespread use of RFID tags, retailers have started to use them for anti-theft along with restocking. The customer can remove the card after purchasing the product. Department stores have installed "smart exit" sensors at customer and employee exits, with technology designed to recognize item numbers on tags.