Deep Learning Based Shopping Automation Using K Means Clustering Algorithm
In current days, people prefers to go shopping malls to purchase their daily needs. Thus shopping mall become an essential part of life. This system is mainly proposed for edible objects like fruits and vegetables. For edible products like vegetables and fruits barcode reader and RFID tags are difficult to use because they have to be stuck on each of the products and weight of each product has to be measured individually. The designed system which includes a camera that identifies the product using deep learning techniques. Load cell is used to measure the weight of the product that is connected to an Arduino. Mat lab software is used for identifying the type of fruits and vegetables. Once the object detection and weight is calculated, the bill is displayed on the LCD(liquified crystal display) along with the price of the item that has been purchased. The fruits and vegetables are identified by using the K-Means algorithm to cluster the images. The designed system will automate shopping by reducing the time in bill generation.