Enhancing the Smart, Digitized Food Supply Chain through Self-Learning and Self-Adaptive Systems

Henrichs, Elia

doi:10.1109/acsos-c52956.2021.00081

Cited by 2 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Identified future work: In order to assist data accessibility, novel and cheaper sensors are developed, enabling them to be integrated into the food packaging [ 92 ]. In conjunction with other related technologies as blockchain, this provides more possibilities to monitor the food’s condition during the later stages [ 124 ]. This leads to a transformation of the FSC with digital twins that potentially offer greater transparency, improved traceability, reduced disruption risk, and optimized processing.…”

Section: Discussionmentioning

confidence: 99%

Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry

Henrichs

Noack

Piedrahita

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

The food industry faces many challenges, including the need to feed a growing population, food loss and waste, and inefficient production systems. To cope with those challenges, digital twins that create a digital representation of physical entities by integrating real-time and real-world data seem to be a promising approach. This paper aims to provide an overview of digital twin applications in the food industry and analyze their challenges and potentials. Therefore, a literature review is executed to examine digital twin applications in the food supply chain. The applications found are classified according to a taxonomy and key elements to implement digital twins are identified. Further, the challenges and potentials of digital twin applications in the food industry are discussed. The survey revealed that the application of digital twins mainly targets the production (agriculture) or the food processing stage. Nearly all applications are used for monitoring and many for prediction. However, only a small amount focuses on the integration in systems for autonomous control or providing recommendations to humans. The main challenges of implementing digital twins are combining multidisciplinary knowledge and providing enough data. Nevertheless, digital twins provide huge potentials, e.g., in determining food quality, traceability, or designing personalized foods.

show abstract

Section: Discussionmentioning

confidence: 99%

Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry

Henrichs

Noack

Piedrahita

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…Zheng et al (2021) proposed a food safety traceability system based on RFID two-dimensional code technology and big data storage technology, which can trace the whole process of food production information and is conducive to epidemic prevention and control [25]. Henrichs (2021) used an adaptive system in the food supply chain to reduce food waste and improve food safety [26]. Anand and Saxena (2022) believed that food safety and quality issues are critical during the COVID-19 pandemic and explored the application of IOT devices for safe-packaged food and frozen food to improve food standards [27].…”

Section: Research On Food Logisticsmentioning

confidence: 99%

Quantitative Analysis of Food Safety Policy—Based on Text Mining Methods

Song

Gholizadeh

Zhuang

2022

Foods

View full text Add to dashboard Cite

Recently, food safety and cold chain food have been closely related to the epidemic. The party and the state have intensified efforts to solve food safety problems and prevent possible epidemic risks. China has issued a series of policies and plans to strengthen food safety supervision to improve the food safety policy system. To our knowledge, little work has studied policy problems of food safety with in-depth quantitative analysis for an extended period. In accordance with the different national policies and regulations for food safety, this paper fills the gap by analyzing the policies and comparing the central and local policies issued in China from 2007–2022. In addition, the Latent Dirichlet Allocation (LDA) topic model and K-Means clustering model are constructed to analyze the content of food safety policies and identify hot topics. Finally, a quantitative analysis of China’s food safety policies is made from four aspects: the number of policy release years, the distribution area, the range of action, and the affiliated institutions. The results show that: (a) there is a partial surge in food safety policies issued in 2007, 2011, and 2017; (b) the local food safety policy has a high inheritance to the central policy content, and the trends of annual publication number are highly consistent; (c) the innovation of different policy contents in the region have their own characteristics; (d) the proportion of compulsory and capacity policies is much more significant than that of other types of policies. This paper provides some novel insights into food safety policies.

show abstract

Enhancing the Smart, Digitized Food Supply Chain through Self-Learning and Self-Adaptive Systems

Cited by 2 publications

References 9 publications

Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry

Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry

Quantitative Analysis of Food Safety Policy—Based on Text Mining Methods

Contact Info

Product

Resources

About