Overview / Usage

Aim of this project is to develop a handheld device, possible one that fits onto the back of a phone, which will then enable to user to detect the freshness of fruits and vegetables that they are buying from a grocery store or taken out of a refrigerator at home.

A bigger, more accurate version can be built as a wall mounted device at a kitchen and the user will be able to scan food items for their freshness before using it - > Adding a much needed meaning to the term Smart kitchen.

Methodology / Approach

Based on published research papers and previous products, we intend to figure out the best parameters that has a direct relation to freshness of fruits and vegetables and possible contamination that might have occurred.

We are focused on finding a generalized method for detection so that we can accurately predict a good variety of fruits and vegetables in a category with a model that is trained only on a subset of the category.

Technologies Used

Intel Python, Sklearn/Tensorflow, Edge Computing using Intel NUC, Spectroscopy.

Collaborators