Intelligent Dynamic Quality Prediction of Chilled Chicken with Integrated IoT Flexible Sensing and Knowledge Rules Extraction
With the enhancement of consumers’ food safety awareness, consumers have become more stringent on meat quality. This study constructs an intelligent dynamic prediction model based on knowledge rules and integrates flexible humidity sensors into the non-destructive monitoring of the Internet of Thing...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
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MDPI AG
2022-03-01
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Series: | Foods |
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Online Access: | https://www.mdpi.com/2304-8158/11/6/836 |
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author | Jinchao Xu Ruiqin Ma Stevan Stankovski Xue Liu Xiaoshuan Zhang |
author_facet | Jinchao Xu Ruiqin Ma Stevan Stankovski Xue Liu Xiaoshuan Zhang |
author_sort | Jinchao Xu |
collection | DOAJ |
description | With the enhancement of consumers’ food safety awareness, consumers have become more stringent on meat quality. This study constructs an intelligent dynamic prediction model based on knowledge rules and integrates flexible humidity sensors into the non-destructive monitoring of the Internet of Things to provide real-time feedback and dynamic adjustments for the chilled chicken cold chain. The optimized sensing equipment can be attached to the inside of the packaging to deal with various abnormal situations during the cold chain, effectively improving the packaging effect. Through correlation analysis of collected data and knowledge rule extraction of critical factors in the cold chain, the established quality evaluation and prediction model achieved detailed chilled chicken quality level classification and intelligent quality prediction. The obtained results show that the accuracy of the prediction model is higher than 90.5%, and all the regression coefficients are close to 1.00. The relevant personnel (workers and cold chain managers) were invited to participate in the performance analysis and optimization suggestion to improve the applicability of the established prediction model. The optimized model can provide a more efficient theoretical reference for timely decision-making and further e-commerce management. |
first_indexed | 2024-03-09T19:51:33Z |
format | Article |
id | doaj.art-c6823bf58b6b4e73b00100126c187313 |
institution | Directory Open Access Journal |
issn | 2304-8158 |
language | English |
last_indexed | 2024-03-09T19:51:33Z |
publishDate | 2022-03-01 |
publisher | MDPI AG |
record_format | Article |
series | Foods |
spelling | doaj.art-c6823bf58b6b4e73b00100126c1873132023-11-24T01:10:39ZengMDPI AGFoods2304-81582022-03-0111683610.3390/foods11060836Intelligent Dynamic Quality Prediction of Chilled Chicken with Integrated IoT Flexible Sensing and Knowledge Rules ExtractionJinchao Xu0Ruiqin Ma1Stevan Stankovski2Xue Liu3Xiaoshuan Zhang4Beijing Laboratory of Food Quality and Safety, College of Engineering, China Agricultural University, Beijing 100083, ChinaNational Research Faculty for Phenotypic and Genotypic Analysis of Model Animals, China Agricultural University, Beijing 100083, ChinaFaculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, SerbiaBeijing Laboratory of Food Quality and Safety, College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, ChinaBeijing Laboratory of Food Quality and Safety, College of Engineering, China Agricultural University, Beijing 100083, ChinaWith the enhancement of consumers’ food safety awareness, consumers have become more stringent on meat quality. This study constructs an intelligent dynamic prediction model based on knowledge rules and integrates flexible humidity sensors into the non-destructive monitoring of the Internet of Things to provide real-time feedback and dynamic adjustments for the chilled chicken cold chain. The optimized sensing equipment can be attached to the inside of the packaging to deal with various abnormal situations during the cold chain, effectively improving the packaging effect. Through correlation analysis of collected data and knowledge rule extraction of critical factors in the cold chain, the established quality evaluation and prediction model achieved detailed chilled chicken quality level classification and intelligent quality prediction. The obtained results show that the accuracy of the prediction model is higher than 90.5%, and all the regression coefficients are close to 1.00. The relevant personnel (workers and cold chain managers) were invited to participate in the performance analysis and optimization suggestion to improve the applicability of the established prediction model. The optimized model can provide a more efficient theoretical reference for timely decision-making and further e-commerce management.https://www.mdpi.com/2304-8158/11/6/836chilled chickenintelligent dynamic prediction modelflexible sensingknowledge rulesquality evaluation standard |
spellingShingle | Jinchao Xu Ruiqin Ma Stevan Stankovski Xue Liu Xiaoshuan Zhang Intelligent Dynamic Quality Prediction of Chilled Chicken with Integrated IoT Flexible Sensing and Knowledge Rules Extraction Foods chilled chicken intelligent dynamic prediction model flexible sensing knowledge rules quality evaluation standard |
title | Intelligent Dynamic Quality Prediction of Chilled Chicken with Integrated IoT Flexible Sensing and Knowledge Rules Extraction |
title_full | Intelligent Dynamic Quality Prediction of Chilled Chicken with Integrated IoT Flexible Sensing and Knowledge Rules Extraction |
title_fullStr | Intelligent Dynamic Quality Prediction of Chilled Chicken with Integrated IoT Flexible Sensing and Knowledge Rules Extraction |
title_full_unstemmed | Intelligent Dynamic Quality Prediction of Chilled Chicken with Integrated IoT Flexible Sensing and Knowledge Rules Extraction |
title_short | Intelligent Dynamic Quality Prediction of Chilled Chicken with Integrated IoT Flexible Sensing and Knowledge Rules Extraction |
title_sort | intelligent dynamic quality prediction of chilled chicken with integrated iot flexible sensing and knowledge rules extraction |
topic | chilled chicken intelligent dynamic prediction model flexible sensing knowledge rules quality evaluation standard |
url | https://www.mdpi.com/2304-8158/11/6/836 |
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