University of Waterloo

Published purpose

Delivery of fresh and frozen foods presents many challenges for supply chain systems, due to the perishable nature of these goods. The global pandemic has revitalized local retail logistics models in light of high demand for the delivery of perishable goods, and to ensure product freshness, safety and security, real-time tracking and monitoring of all operational elements along the production, packaging and distribution delivery chain has become extremely important. This project seeks to develop sophisticated, real-time traceability associated with delivery logistics. Built on extensive benchmarked datasets and artificial intelligence of things technology, this project will deploy training and testing datasets to design, develop, and validate a set of self-learning algorithms for assessing freshness and integrity of the products along a plausible logistics value chain. In particular, this project focuses on developing AI-enabled models for monitoring the freshness of goods along the production and delivery chain. In this project, predictive models will be developed, tested, and validated, and at least two full use-cases for the delivery of fresh products from production to end-use will be designed. The project outcome will be an AI-enabled algorithm that collects real-time data that can be deployed in a field-test setting.