Smart Grocery Grading System

Abstract

This paper discusses a Smart Grocery Grading System, capable of performing non-destructive testing on produce and assessing their freshness based on a number of key factors such as discolouration, external bruising etc. The system works on the principle that an image of the fruit or vegetable is captured and fed to the trained neural network. The network then assesses the image based on its training parameters and determines if the fruit or vegetable is fresh or rotten. The primary objective of this system is to provide the general populace with an accurate means of estimating the edibility of grocery before purchasing it. The system is designed such that it is cost effective and is capable of returning accurate results in real time.