TomatVision App

Deskripsi

*Background: The tomato sauce industry requires high-quality tomatoes to maintain product standards. Traditionally, quality control is manual, labor-intensive, and error-prone, leading to inconsistencies and higher costs. Advances in AI and computer vision provide an opportunity to automate this process. *Problem Statement: Firstly, there is a prevalent problem where users discover that spoiled tomatoes are being used in ketchup production, leading to concerns about food safety and product quality. Secondly, the process of sorting tomatoes for production is highly time-consuming and labor-intensive, which significantly hampers operational efficiency. Lastly, the current method of selecting tomatoes is manual, lacking technological assistance. *Solution Overview: TomatVision App uses Convolutional Neural Networks (CNN) algorithm to automate tomato classification into "Pass" and "Failed" categories. It also uses camera integrated with software to automate the tomato sorting process.