Faculty:Swarup Bhunia
Project Description:Like any other supply chain, food supply chain also maintains multiple entities for sending food from producer to consumer. Throughout the process, if logistics are not maintained properly, food quality may degrade. Degradation can be of many types, for instance: texture degradation, adulteration with harmful chemical, unexpected appearance of harmful ingredient etc. Therefore, there is a need of smart, user-friendly, and inexpensive device to continuously monitor the quality of food throughout the whole process. Spectroscopic methods (i.e. NQR, NMR, NIR) are excellent candidates to identify presence of harmful particles in food and B-mode ultrasound for optical analysis on objects. Therefore, the ultimate goal of this project is to build a smart multimodal system that will collect signatures from food when scanned and connect to cloud to get reference signatures as well as data analysis. Once necessary data are collected, they will be analyzed by machine learning based approaches to make instant decisions about the quality of that food.