AI-enabled Safe and Efficient Food Supply Chain

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

AI-enabled Safe and Efficient Food Supply Chain

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

University of Lincoln

Research output: Other contribution

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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 language	English
Type	REF 2021 impact case
Publisher	Research Excellence Framework (REF) 2021
Number of pages	5
Publication status	Published - 22 Jun 2022

Bibliographical note

REF 2021 impact case

Keywords

Machine Learning
Industry

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Impact case study - University of Lincoln - 11 - AI-enabled Safe and Efficient
Officially published on REF 2021 website
Final published version, 232 KB

https://results2021.ref.ac.uk/impact/6399af09-1465-4629-bd02-f46b90077dc6?page=1

Cite this

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title = "AI-enabled Safe and Efficient Food Supply Chain",

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T1 - AI-enabled Safe and Efficient Food Supply Chain

AU - Kollias, Stefanos

AU - Ye, Xujiong

AU - Yu, Miao

AU - Duan, Wenting

AU - Leontidis, Georgios

AU - Swainson, Mark

AU - Pearson, Simon

N1 - REF 2021 impact case

PY - 2022/6/22

Y1 - 2022/6/22

N2 - 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.

AB - 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.

KW - Machine Learning

KW - Industry

M3 - Other contribution

PB - Research Excellence Framework (REF) 2021

ER -

AI-enabled Safe and Efficient Food Supply Chain

Abstract

Bibliographical note

Keywords

UN SDGs

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Cite this