AI-enabled Safe and Efficient Food Supply Chain

Stefanos Kollias, Xujiong Ye, Miao Yu, Wenting Duan, Georgios Leontidis, Mark Swainson, Simon Pearson

Research output: Other contribution

4 Downloads (Pure)

Abstract

Food and drink processing is the largest manufacturing sector in the UK, but faces significant challenges around safety, waste, and energy use. AI offers a transformative solution, and Deep learning (DL) research by the Mlearn Research Group in the School of Computer Science (SoCS) has innovated AI-enabled efficient and safe food chains in energy management and food labeling. In collaboration with sector partners, Mlearn’s DL research has 1) optimised energy consumption across a large network of retail refrigeration systems, with financial benefits and reduced pressure on the National Grid, and 2) ensured safety of packaged food by enabling 100% inspection of the use-by date for consumption along the food production line.
Original languageEnglish
TypeREF 2021 impact case
PublisherResearch Excellence Framework (REF) 2021
Number of pages5
Publication statusPublished - 22 Jun 2022

Keywords

  • Machine Learning
  • Industry

Fingerprint

Dive into the research topics of 'AI-enabled Safe and Efficient Food Supply Chain'. Together they form a unique fingerprint.

Cite this