THE USE OF BLOCKCHAIN IN THE MANAGEMENT OF COVID-19 VACCINE DATA

ABSTRACT - The ongoing COVID-19 pandemic has disrupted nearly every sector of the world economy. The recently discovered vaccine has promised a return to normalcy. Since traditional database storage systems can be tampered with quickly, the incorporation of blockchain would preclude the limitations of conventional database systems. This paper thus discusses the use of blockchain technology in managing the COVID-19 vaccine data to ensure credibility, safety, security, and transparency. Keywords - Blockchain technology, COVID-19 vaccine data, and vaccine supply chain

IoT technologies for wine supply chain traceability: Potential application in the Southern Apulia Region (Italy)

The high value and volume of Italian wine production determines a strong stimulus for counterfeiting, which generates negative consequences for grape growers, winemakers and consumers. In this context, IoT technologies and the blockchain can serve as tools to ensure traceability, transparency and efficiency along the whole wine supply chain. Using primary data collected through interviews to the main grape growers and wineries involved in the wine supply chain in the Southern Apulia Region and secondary data, acquired from previous scientific literature, the study proposes a framework for the traceability and efficiency of the wine supply chain based on a combination of blockchain, Radio-Frequency Identification (RFID) and Near Field Communication (NFC) tags, Serial Shipping Container Codes (SSCC) and Quick Response (QR) codes. The developed framework allows for the systematic storage of information about commodities and processes throughout the supply chain, from grape growers to wine consumption and packaging disposal and/or reuse (forward and reverse flows). In addition, it ensures the transparency, safety, and security of all processes involved within the wine supply chain, serving as a quality information management tool. The information collected along the wine supply chain is entered into the management system by farmers, winemakers and bottlers and is accessible to all of them, while the distributors, consumers and the bottle reverse logistics operators, can only consult all of the information stored on the blockchain in order to know the origin, the quality, the processing and the authenticity of wines, without being able to enter data and/or modify the existent information

A blockchain-based evaluation approach to analyse customer satisfaction using AI techniques

Due to technological advancements and consumer demands, online shopping creates new features and adapts to new standards. A robust customer satisfaction prediction model concerning trust and privacy platforms can encourage an organization to make better decisions about its service and quality. This study presented an approach to predict consumer satisfaction using the blockchain-based framework combining the Multi-Dimensional Naive Bayes-K Nearest Neighbor (MDNB-KNN) and the Multi-Objective Logistic Particle Swarm Optimization Algorithm (MOL-PSOA). A regression model is employed to quantify the impact of various production factors on customer satisfaction. The proposed method yields better levels of measurement for customer satisfaction (98%), accuracy (95%), necessary time (60%), precision (95%), and recall (95%) compared to existing studies. Measuring consumer satisfaction with a trustworthy platform facilitates to development of the conceptual and practical distinctions influencing customers' purchasing decisions.publishedVersio

Pharmaceutical enterprises drug quality strategy Moran analysis considering government supervision and new media participation

The improvement of drug quality requires not only the supervision of government, but also the participation of new media. Therefore, this paper considers the impact of government regulation and new media reports on pharmaceutical enterprises, constructs a Moran Process evolutionary game model, and analyzes the evolution trajectory of pharmaceutical enterprises' choice of drug quality improvement strategy and drug cost reduction strategy. We obtain the conditions for the two strategies to achieve evolutionary stability under the dominance of external factors and the dominance of expected returns. To verify the theoretical results, we conduct a numerical simulation by the software MATLAB 2021b. The results show that, first of all, when the government penalty is high, the drug quality improvement strategy tends to become an evolutionary stable solution, increasing the penalty amount will help promote the improvement of drug quality. What's more, when the government penalty is low and the new media influence is low, the drug cost reduction strategy is easier to dominate. The higher the new media influence, the higher the probability that pharmaceutical enterprises choose the drug quality improvement strategy. Thirdly, when the number of pharmaceutical enterprises is lower than a threshold, the drug quality improvement strategy is easier to dominate. Finally, the drug quality improvement strategy is dominant when the quality cost factor is low and the government penalty is high, the drug cost reduction strategy is dominant when the quality cost factor is high and the government penalty is low. Above all, this paper provides countermeasures and suggestions for the drug quality improvement of pharmaceutical enterprises in practice

COVID-19 Antibody Test/Vaccination Certification There’s an app for that

Goal: As the Coronavirus Pandemic of 2019/2020 unfolds, a COVID-19 ‘Immunity Passport’ has been mooted as a way to enable individuals to return back to work. While the quality of antibody testing, the avail- the ability of vaccines, and the likelihood of even attaining COVID-19 immunity continue to be researched, we address the issues involved in providing tamper-proof and privacy-preserving certification for test results and vaccinations. Methods: We developed a prototype mobile phone app and requisite decentralized server architecture that facilitates instant verification of tamper-proof test results. Personally identifiable information is only stored at the user’s discretion, and the app allows the end-user selectively to present only the specific test result with no other personal information revealed. The architecture, designed for scalability, relies upon (a) the 2019 World Wide Web Consortium standard called ‘Verifiable Credentials’, (b) Tim Berners-Lee’s decentralized personal data platform ‘Solid’, and (c) a Consortium Ethereum-based blockchain. Results: Our mobile phone app and decentralized server architecture enable the mixture of verifiability and privacy in a manner derived from public/private key pairs and digital signatures, generalized to avoid restrictive ownership of sensitive digital keys and/or data. Benchmark performance tests show it to scale linearly in the worst case, as significant processing is done locally on each app. For the test certificate Holder, Issuer (e.g. healthcare staff, pharmacy) and Verifier (e.g. employer), it is ‘just another app’ which takes only minutes to use. Conclusions: The app and decentralized server architecture offer a prototype proof of concept that is readily scalable, applicable generically, and in effect ‘waiting in the wings’ for the biological issues, plus key ethical issues raised in the discussion section, to be resolved

Advancing sustainability in the food and nutrition system: a review of artificial intelligence applications

Promoting sustainability in food and nutrition systems is essential to address the various challenges and trade-offs within the current food system. This imperative is guided by key principles and actionable steps, including enhancing productivity and efficiency, reducing waste, adopting sustainable agricultural practices, improving economic growth and livelihoods, and enhancing resilience at various levels. However, in order to change the current food consumption patterns of the world and move toward sustainable diets, as well as increase productivity in the food production chain, it is necessary to employ the findings and achievements of other sciences. These include the use of artificial intelligence-based technologies. Presented here is a narrative review of possible applications of artificial intelligence in the food production chain that could increase productivity and sustainability. In this study, the most significant roles that artificial intelligence can play in enhancing the productivity and sustainability of the food and nutrition system have been examined in terms of production, processing, distribution, and food consumption. The research revealed that artificial intelligence, a branch of computer science that uses intelligent machines to perform tasks that require human intelligence, can significantly contribute to sustainable food security. Patterns of production, transportation, supply chain, marketing, and food-related applications can all benefit from artificial intelligence. As this review of successful experiences indicates, artificial intelligence, machine learning, and big data are a boon to the goal of sustainable food security as they enable us to achieve our goals more efficiently

Applying blockchain technology to improve agri-food traceability: A review of development methods, benefits and challenges

Traceability plays a vital role in food quality and safety management. Traditional Internet of Things (IoT) traceability systems provide the feasible solutions for the quality monitoring and traceability of food supply chains. However, most of the IoT solutions rely on the centralized server-client paradigm that makes it difficult for consumers to acquire all transaction information and to track the origins of products. Blockchain is a cutting-edge technology that has great potential for improving traceability performance by providing security and full transparency. However, the benefits, challenges and development methods of blockchain-based food traceability systems are not yet fully explored in the current literature. Therefore, the main aim of this paper is to review the blockchain technology characteristics and functionalities, identify blockchain-based solutions for addressing food traceability concerns, highlight the benefits and challenges of blockchain-based traceability systems implementation, and help researchers and practitioners to apply blockchain technology based food traceability systems by proposing an architecture design framework and suitability application analysis flowchart of blockchain based food traceability systems. The results of this study contribute to better understanding and knowledge on how to improve the food traceability by developing and implementing blockchain-based traceability systems. The paper provides valuable information for researchers and practitioners on the use of blockchain-based food traceability management and has a positive effect on the improvement of food sustainability

Blockchain-Empowered Mobile Edge Intelligence, Machine Learning and Secure Data Sharing

Driven by recent advancements in machine learning, mobile edge computing (MEC) and the Internet of things (IoT), artificial intelligence (AI) has become an emerging technology. Traditional machine learning approaches require the training data to be collected and processed in centralized servers. With the advent of new decentralized machine learning approaches and mobile edge computing, the IoT on-device data training has now become possible. To realize AI at the edge of the network, IoT devices can offload training tasks to MEC servers. However, those distributed frameworks of edge intelligence also introduce some new challenges, such as user privacy and data security. To handle these problems, blockchain has been considered as a promising solution. As a distributed smart ledger, blockchain is renowned for high scalability, privacy-preserving, and decentralization. This technology is also featured with automated script execution and immutable data records in a trusted manner. In recent years, as quantum computers become more and more promising, blockchain is also facing potential threats from quantum algorithms. In this chapter, we provide an overview of the current state-of-the-art in these cutting-edge technologies by summarizing the available literature in the research field of blockchain-based MEC, machine learning, secure data sharing, and basic introduction of post-quantum blockchain. We also discuss the real-world use cases and outline the challenges of blockchain-empowered intelligence

Last Mile Distribution of COVID-19 Vaccines: A Cold Chain Logistical Challenge

The COVID-19 pandemic is a global health and humanitarian crisis that has wreaked havoc on economies and industries around the world. This study aims to address the distribution of the COVID-19 vaccines at the last mile by evaluating the vaccine supply chain and how it can be effectively utilized to address the last mile distribution of the COVID-19 vaccines through simulation. The first part includes a systematic literature review and bibliometric study of vaccine supply chain and cold chain logistics studies conducted in the last decade. The second part examines the distribution of COVID-19 vaccines in Norway as a case study. The study develops a two-stage optimization simulation method to analyse and improve the logistical performance of the COVID-19 vaccine distribution in Inland County, Norway. The study analyses the impact of fleet size and the use of heterogeneous vehicles in the last mile distribution network on some key performance indicators. The findings from the study reveal that the service level, transportation costs and environmental performance of the vaccine logistics system are significantly influenced by routing decisions, fleet size, fleet composition and the types of heterogeneous vehicles used. Based on the findings from the study, some managerial insights are outlined to help logistics managers better understand the interactions between the key parameters of a cold chain vaccine distribution system

Artificial intelligence and blockchain integration in business: Trends from a bibliometric-content analysis

YesArtificial intelligence (AI) and blockchain are the two disruptive technologies emerging from the Fourth Industrial Revolution (IR4.0) that have introduced radical shifts in the industry. The amalgamation of AI and blockchain holds tremendous potential to create new business models enabled through digitalization. Although research on the application and convergence of AI and blockchain exists, our understanding of the utility of its integration for business remains fragmented. To address this gap, this study aims to characterize the applications and benefits of integrated AI and blockchain platforms across different verticals of business. Using bibliometric analysis, this study reveals the most influential articles on the subject based on their publications, citations, and importance in the intellectual network. Using content analysis, this study sheds light on the subject’s intellectual structure, which is underpinned by four major thematic clusters focusing on supply chains, healthcare, secure transactions, and finance and accounting. The study concludes with 10 application areas in business that can benefit from these technologies