Grants and Contributions:
Title:
Development of self-learning algorithms for monitoring and assessing integrity of goods in Internet of Things based urban logistics
Agreement Number:
973380
Agreement Value:
$77,000.00
Agreement Date:
Jun 1, 2021 - Jan 30, 2026
Description:
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.
Organization:
National Research Council Canada
Expected Results:
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Location:
Waterloo, Ontario, CA N2L 3G1
Reference Number:
172-2021-2022-Q1-973380
Agreement Type:
Grant
Report Type:
Grants and Contributions
Recipient Business Number:
119260685
Recipient Type:
Academia
Additional Information:
This agreement has been amended 2 time(s). The end date of this agreement has been modified by 364 days.
Amendment Date
Jan 17, 2025
Recipient's Legal Name:
University of Waterloo
Federal Riding Name:
Waterloo
Federal Riding Number:
35114
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Purpose:
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
NAICS Code:
541710
Amendments: