Fruit Freshness Detection Using IoT and Machine Learning

This project aims to enhance the precision and efficiency of detecting fruits rot. It achieves this by utilizing sensors to detect the gases emitted by the fruits and analyzing images with machine learning models such as VGG 16 to obtain a more comprehensive evaluation of their freshness level. The models have trained on extensive images and sensor data datasets, which allows for precise identification of varying degrees of fruit freshness. Real-time data analysis and reporting to a connected technological ecosystem enables prompt monitoring of the fruits' freshness. If implemented, this project could decrease wastage and guarantee that top-quality fruits are delivered to their intended destinations, benefiting the fruit transportation sector.