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Monitoring potato waste in food manufacturing using image processing and Internet of Things approach

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journal contribution
posted on 13.06.2019, 13:40 authored by Sandeep Jagtap, Chintan Bhatt, Jaydeep Thik, Shahin RahimifardShahin Rahimifard
Approximately one-third of the food produced globally is spoiled or wasted in the food supply chain (FSC). Essentially, it is lost before it even reaches the end consumer. Conventional methods of food waste tracking relying on paper-based logs to collect and analyse the data are costly, laborious, and time-consuming. Hence, an automated and real-time system based on the Internet of Things (IoT) concepts is proposed to measure the overall amount of waste as well as the reasons for waste generation in real-time within the potato processing industry, by using modern image processing and load cell technologies. The images captured through a specially positioned camera are processed to identify the damaged, unusable potatoes, and a digital load cell is used to measure their weight. Subsequently, a deep learning architecture, specifically the Convolutional Neural Network (CNN), is utilised to determine a potential reason for the potato waste generation. An accuracy of 99.79% was achieved using a small set of samples during the training test. We were successful enough to achieve a training accuracy of 94.06%, a validation accuracy of 85%, and a test accuracy of 83.3% after parameter tuning. This still represents a significant improvement over manual monitoring and extraction of waste within a potato processing line. In addition, the real-time data generated by this system help actors in the production, transportation, and processing of potatoes to determine various causes of waste generation and aid in the implementation of corrective actions.

Funding

The Engineering and Physical Sciences Research Council (EPSRC) Centre for Innovative Manufacturing in Food [Reference: EP/K030957/1].

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Sustainability

Volume

11

Issue

11

Citation

JAGTAP, S. ... et al, 2019. Monitoring potato waste in food manufacturing using image processing and Internet of Things approach. Sustainability, 11 (11), 3173.

Publisher

MDPI AG © The authors

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

03/06/2019

Publication date

2019-06-05

Notes

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

eISSN

2071-1050

Language

en