Automatized Food Quality Detection and Processing System Using Neural Networks

In today's world, food processing industries play a vital role either directly or indirectly in human's sustenance. Majority of the food processing industries do still hinge on direct human intervention. The quality of food can be evaluated using computer vision which provides a solution through an automatized nondestructive and cost effective approach. This paper proposes a sustenance quality recognizing and reviewing framework dependent on OpenCV python library. The Convolution Neural Network (CNN) is implemented to perform the tasks of fruit type recognition and its quality detection through precise, dependable, reliable and quantitative data. The proposed system comprises of microcontroller, sensors, a camera and a conveyor belt setup to segregate the fruits. To preserve the quality of fruits for longer duration the storage unit environment condition is measured using sensors and the data is sent over the cloud based on the technology of Internet of Things.