Research on Intelligent Supervision and Application System of Food Traceability Based on Blockchain and Artificial intelligence

Ling, Caijin; Zeng, Ting; Shao‐Horn, Yang

doi:10.1109/iciba52610.2021.9688295

Cited by 6 publications

(7 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These advanced algorithms help enhance system scalability and optimize energy consumption. AI, supported by blockchain, can identify security vulnerabilities, thereby bolstering optimization [ 76 ]. As a robust platform, blockchain channels critical data to AI, refining decision-making accuracy and ensuring a secure, decentralized AI system.…”

Section: Findings and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Blockchain-Based Frameworks for Food Traceability: A Systematic Review

Ellahi

Wood

Bekhit

2023

Foods

View full text Add to dashboard Cite

With the rise of globalization and technological competition, the food supply chain has grown more complex due to the multiple players and factors involved in the chain. Traditional systems fail to offer effective and reliable traceability solutions considering the increasing requirement for accountability and transparency in the food supply chain. Blockchain technology has been claimed to offer the food industry a transformative future. The inherent features of blockchain, including immutability and transparency, create a dependable and secure system for tracking food products across the whole supply chain, ensuring total control over their traceability from the origin to the final consumer. This research offers a comprehensive overview of multiple models to understand how the integration of blockchain and other digital technologies has transformed the food supply chain. This comprehensive systematic review of blockchain-based food-supply-chain frameworks aimed to uncover the capability of blockchain technology to revolutionize the industry and examined the current landscape of blockchain-based food traceability solutions to identify areas for improvement. Furthermore, the research investigates recent advancements and investigates how blockchain aligns with other emerging technologies of Industry 4.0 and Web 3.0. Blockchain technology plays an important role in improving food traceability and supply-chain operations. Potential synergies between blockchain and other emerging technologies of Industry 4.0 and Web 3.0 are digitizing food supply chains, which results in better management, automation, efficiencies, sustainability, verifiability, auditability, accountability, traceability, transparency, tracking, monitoring, response times and provenance across food supply chains.

show abstract

Section: Findings and Discussionmentioning

confidence: 99%

“…As a robust platform, blockchain channels critical data to AI, refining decision-making accuracy and ensuring a secure, decentralized AI system. This collaboration heightens food traceability [ 76 ].…”

Section: Findings and Discussionmentioning

confidence: 99%

Blockchain-Based Frameworks for Food Traceability: A Systematic Review

Ellahi

Wood

Bekhit

2023

Foods

View full text Add to dashboard Cite

show abstract

“…It significantly improves the food supply chain's transparency and efficiency to rebuild the consumer's confidence in the food industry. Further, in [62], the authors highlighted several limitations in the food supply chain, such as forged products, damage to food commodities, security, and damage to consumer rights. Therefore, the authors employed blockchain-and AI-based models to enhance food traceability, scalability, and monitoring.…”

Section: Food Traceabilitymentioning

confidence: 99%

Blockchain Adoption to Secure the Food Industry: Opportunities and Challenges

et al. 2022

View full text Add to dashboard Cite

With the growth in food products’ usage, ensuring their quality and safety has become progressively difficult. Specifically, food traceability turns out to be a very critical task for retailers, sellers, consumers, surveillance authorities, and other stakeholders in the food supply chain system. There are requirements for food authenticity verification (correct declaration of cultivation, origin, and variety), quality checks (e.g., justification for higher prices), and preventing food products from fraudsters in the food industry. The ubiquitous and promising technology of blockchain ensures the traceability of food trade networks with high potential and handles the aforementioned issues. Blockchain makes the food industry more transparent at all levels by storing data immutably and enabling quick tracking across the stages of the food supply chain. Hence, commodities, stakeholders, and semi-finished food items can be recognized significantly faster. Motivated by these facts, in this paper, we present an in-depth survey of state-of-the-art approaches to the food industry’s security, food traceability, and food supply chain management. Further, we propose a blockchain-based secure and decentralized food industry architecture to alleviate security and privacy aspects and present a comprehensive solution taxonomy for a blockchain-based food industry. Then, a comparative analysis of existing approaches with respect to various parameters, i.e., scalability, latency, and food quality, is presented, which facilitates the end-user in selecting approaches based on the merits over other approaches. Finally, we provide insights into the open issues and research challenges with concluding remarks.

show abstract

“…Significant difficulties are presented by the secrecy of many algorithmic systems, which raises questions about fairness, responsibility, and ethical consequences. The purpose of this introduction is to set the stage for our investigation into the [1] contribution that interpretable models can make to overcoming these issues and eventually promoting ethical accountability in algorithmic decision-making.In our daily lives [2], algorithms are already pervasive and have an impact on everything from loan approvals to hiring decisions to medical diagnoses. However, the inner workings of these algorithms remain a mystery to the people impacted by their decisions even as they make increasingly significant decisions.…”

Section: Introductionmentioning

confidence: 99%

Transparency in Algorithmic Decision-making: Interpretable Models for Ethical Accountability

Raja Kumar,

Kalnawat,

Pawar

et al. 2024

E3S Web Conf.

View full text Add to dashboard Cite

Concerns regarding their opacity and potential ethical ramifications have been raised by the spread of algorithmic decisionmaking systems across a variety of fields. By promoting the use of interpretable machine learning models, this research addresses the critical requirement for openness and moral responsibility in these systems. Interpretable models provide a transparent and intelligible depiction of how decisions are made, as opposed to complicated black-box algorithms. Users and stakeholders need this openness in order to understand, verify, and hold accountable the decisions made by these algorithms. Furthermore, interpretability promotes fairness in algorithmic results by making it easier to detect and reduce biases. In this article, we give an overview of the difficulties brought on by algorithmic opacity, highlighting how crucial it is to solve these difficulties in a variety of settings, including those involving healthcare, banking, criminal justice, and more. From linear models to rule-based systems to surrogate models, we give a thorough analysis of interpretable machine learning techniques, highlighting their benefits and drawbacks. We suggest that incorporating interpretable models into the design and use of algorithms can result in a more responsible and moral application of AI in society, ultimately benefiting people and communities while lowering the risks connected to opaque decision-making processes.

show abstract

Research on Intelligent Supervision and Application System of Food Traceability Based on Blockchain and Artificial intelligence

Cited by 6 publications

References 8 publications

Blockchain-Based Frameworks for Food Traceability: A Systematic Review

Blockchain-Based Frameworks for Food Traceability: A Systematic Review

Blockchain Adoption to Secure the Food Industry: Opportunities and Challenges

Transparency in Algorithmic Decision-making: Interpretable Models for Ethical Accountability

Contact Info

Product

Resources

About