Blockchain Papers

Yansheng Chen, Jian Pu, Yin Zhang, Jie Li · 6 authors

No abstract is available for this record.

Kathirvel Ayyaswamy, A. K. Naren, B. Santhoshi, C. P. Maheswaran

By 2027, the blockchain market will have a valuation of 163 billion US dollars. In fact, a firm may find it too much to comprehend and use the technology that has taken off. This demonstrates the promise of decentralized technology and the undeniable influence of blockchain on business across many industries. These days, businesses use blockchain technology and its various features, as ICOs and smart contracts, for a variety of objectives that are related to their daily operations. These days, businesses use blockchain technology and its various features, like ICOs and smart contracts, for a variety of objectives that are related to their daily operations. Because of these built-in characteristics, blockchain is now used in a number of sectors, including real estate, finance, agriculture field, healthcare sector, education institutions, design and manufacturing unit, and retail shopping, etc.

Mohamed Nour El-Din, João Poças Martins, Nuno Ramos, Pedro F. Pereira

Energy performance-based contracts (EPCs) offer a promising solution for enhancing the energy performance of buildings, which is an overarching step towards achieving Net Zero Carbon Buildings, addressing climate change and improving occupants’ comfort. Despite their potential, their execution is constrained by difficulties that hinder their diffusion in the architecture, engineering, construction, and operation industry. Notably, the Measurement and Verification process is considered a significant impediment due to data sharing, storage, and security challenges. Nevertheless, there have been minimal efforts to analyze research conducted in this field systematically. A systematic analysis of 113 identified journal articles was conducted to fill this gap. A paucity of research tackling the utilization of digital technologies to enhance the implementation of EPCs was found. Consequently, this article proposes a framework integrating Digital Twin and Blockchain technologies to provide an enhanced EPC execution environment. Digital Twin technology leverages the system by monitoring and evaluating energy performance in real-time, predicting future performance, and facilitating informed decisions. Blockchain technology ensures the integrity, transparency, and accountability of information. Moreover, a private Blockchain infrastructure was originally introduced in the framework to eliminate high transaction costs related to on-chain storage and potential concerns regarding the confidentiality of information in open distributed ledgers.

Seyed Mojtaba Hosseini Bamakan, Saeed Banaeian Far

The fourth industrial revolution has significantly increased the adoption of Digital Twins (DTs) across various sectors, including intelligent manufacturing, automation, logistics, and medical analysis. Despite substantial progress in deploying DT projects, numerous challenges remain, such as managing distributed data flows, protecting commercial confidentiality, securing intellectual property, and ensuring privacy and security. This research introduces a novel approach to addressing these challenges by leveraging blockchain and Web3 technologies, including non-fungible tokens (NFTs) and Distributed Autonomous Organizations (DAOs). The study aims to develop a distributed, tamper-proof DT cooperation platform that facilitates traceable and trustworthy data sharing while preserving intellectual property rights and enabling decentralized governance. This platform enhances idea and invention ownership, promotes collective decision-making through consensus protocols, and explores innovative solutions like blockchain-based federated learning and efficient DT project fundraising tools. Relying on security models and analysis tools, this study addresses several important security analysis methods/tools/models (e.g., random oracle model, BAN logic, AVISPA tool, and TAMARIN prover) that are known as practical analysis methods. They can strongly prove every claimed security feature of DT projects. The proposed solutions set the stage for future academic and industrial advancements, supported by a comprehensive SWOT (Strongness - Weakness - Opportunity - Threat) analysis, and outline potential future research directions.

Raja Lavanya, G. Bhavani, C. Santhiya, G. Vinoth Chakkaravarthy · 5 authors

With the advent of the Internet of Things (IoT), a new transformation is predominant in the manufacturing industry, termed Industry 4.0. The revolution of IoT with artificial intelligence, Web3, robotics, and automation has transformed the traditional manufacturing system into a smart manufacturing system (SMS) by adding an intelligent component capable of automatic data collection through using sensors, processing data autonomously, and controlling machines remotely. However, adding automated intelligence, autonomous systems, and real-time data processing presents an insecure surface to cyber attackers to penetrate these cyber-physical systems (CPSs) and cause physical damage. This chapter presents a detailed discussion of cyber threats and incidents in the intelligent manufacturing industry, along with the available acceptable mitigation strategies. A taxonomy of cyber attacks on intelligent manufacturing systems clearly shows the difference between information technology threats and smart manufacturing cyber-threats. A detailed discussion on the limitations of SMSs in implementing cyber security is presented. Finally, some innovative machine learning–based security mechanisms (ML-based intrusion detection systems) are discussed that promise to detect anomalies/intrusions in such systems.

Mirna Ibrahim

Green supply chain management (GSCM) integrates environmental considerations into supply chain functions from product design to end-of-life management. This chapter examines the emerging applications of artificial intelligence (AI) for advancing sustainability across supply chain operations and decision-making. Specifically, it reviews the use of AI-powered analytics, optimization algorithms, machine learning systems, and distributed ledgers for enabling circular resource flows across global value chains. The chapter also critically evaluates the successes, limitations, risks, and ethical considerations of current AI applications in GSCM. Challenges related to data quality, algorithmic bias, job automation risks, and operational integration complexities are discussed, along with mitigation strategies. Case studies demonstrating AI's impact on solving real-world supply chain sustainability issues are incorporated. The chapter broadens the discussion to encompass economic, social, and environmental dimensions of sustainability, as well as AI's role in enhancing supply chain resilience.

Ramiz Salama, Fadi Al‐Turjman

The fusion of blockchain technology and artificial intelligence (AI) promises game-changing solutions for cybersecurity and global value chains (GVCs) as the digital landscape continues to change. This study examines how AI and blockchain technology are being used in novel ways to protect digital assets and improve the effectiveness and resilience of GVCs. Cybersecurity is about to undergo a revolution thanks to AI and its enhanced analytics and machine learning capabilities. This study investigates the real-time risk mitigation capabilities of AI-driven threat detection, predictive analysis, and automated incident response systems. Additionally, the importance of AI in preserving the confidentiality and integrity of data within GVCs is highlighted, providing information on preventative security measures. Blockchain technology is redefining trust and transparency in GVCs because of its decentralized and irreversible ledger. This study examines the use of smart contracts for automated compliance, blockchain for supply chain provenance, and safe data sharing across GVC stakeholders. It emphasizes how blockchain technology has the potential to improve traceability and lower fraud in GVCs. In the context of cybersecurity and GVCs, the relationship between AI and blockchain is examined, demonstrating how AI may improve blockchain security through anomaly detection and consensus methods. Additionally, the importance of blockchain in improving the reliability of AI algorithms and data integrity is investigated, highlighting the influence of these factors taken together on future GVC and cybersecurity ecosystems. To demonstrate the real-world uses of AI and blockchain in tackling cybersecurity threats and improving GVC operations, case studies and developing use cases from a variety of industries are given. The chapter also covers the ethical issues, regulatory difficulties, and potential adoption hurdles that must be overcome for a successful implementation. The transformational potential of AI and blockchain technology in influencing the future of cybersecurity and GVCs is highlighted by this research, in its conclusion. Organizations may proactively strengthen their digital defences, improve supply chain resilience, and open up new avenues for safe and effective international trade by utilizing the synergies between these technologies.

Trung Quang Khuc, Viet Thanh Nguyen, Sy Tien

Purpose The purpose of this study is to identify the key barriers to the adoption of blockchain technology (BCT) in the construction industry. This investigation seeks to understand the challenges that hinder the implementation of blockchain in this sector. Design/methodology/approach The study begins with a comprehensive review of relevant literature to identify the main barriers to blockchain adoption in construction. It then uses an integrated approach using total interpretive structural modeling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement to investigate the interrelationships among these barriers. In addition, the decision-making trial and evaluation laboratory (DEMATEL) method is used to establish cause-and-effect relationships between the identified barriers. Findings The study’s integrated TISM and DEMATEL methodology reveals several crucial barriers to blockchain adoption in the construction industry, including regulatory uncertainty, data privacy and security concerns, limited knowledge and expertise and dependence on blockchain operators. It also identifies scalability issues, uncertain benefits and lack of collaboration as dependent barriers, influenced by other identified barriers. Originality/value This study contributes original value by applying an integrated methodological approach to understand the complex interrelationships and dependencies among barriers to blockchain adoption in the construction industry. The findings provide decision-makers with insights to prioritize and effectively manage the key driving barriers, enhancing the understanding and strategic planning for blockchain implementation in this sector.

Midhun Xavier, Sandeep Patil, Valeriy Vyatkin

This paper presents a novel approach for tracking products and processes within industrial multi-agent control systems by leveraging blockchain technology. The suggested solution facilitates the recording and validation of every step involved in creating a tailored product through the utilization of Ethereum-based smart contracts. The OWL ontology is used to describe agents and their capabilities and these software agents interact with IEC 61499 function blocks for process execution. The software agents record process events at each stage on the blockchain and the latter smart contract helps to trace and verify these process sequences of the customised product.

Xiaozhi Ma, Wenbo Du, Lingyue Li, Jing Liu · 5 authors

Abstract The integration of Blockchain Technology (BT) with Digital Twins (DTs) is becoming increasingly recognized as an effective strategy to enhance trust, interoperability, and data privacy in virtual spaces such as the metaverse. Although there is a significant body of research at the intersection of BT and DTs, a thorough review of the field has not yet been conducted. This study performs a systematic literature review on BT and DTs, using the CiteSpace analytic tool to evaluate the content and bibliometric information. The review covers 976 publications, identifying the significant effects of BT on DTs and the integration challenges. Key themes emerging from keyword analysis include augmented reality, smart cities, smart manufacturing, cybersecurity, lifecycle management, Ethereum, smart grids, additive manufacturing, blockchain technology, and digitalization. Based on this analysis, the study proposes a development framework for BT-enhanced DTs that includes supporting technologies and applications, main applications, advantages and functionalities, primary contexts of application, and overarching goals and principles. Additionally, an examination of bibliometric data reveals three developmental phases in cross-sectional research on BT and DTs: technology development, technology use, and technology deployment. These phases highlight the research field’s evolution and provide valuable direction for future studies on BT-enhanced DTs.

Haya R. Hasan, Mohammad Madine, Ahmad Musamih, Raja Jayaraman · 7 authors

Recent years have witnessed the emergence of digital twins in the industrial metaverse, significantly transforming sectors such as manufacturing, automotive, oil and gas, and gaming. As a result, these sectors have experienced increased efficiency, innovation, and revolutionary solutions. Non-fungible tokens (NFTs) have the potential to enhance digital twins in the industrial metaverse by offering opportunities for monetization, traceability, and tracking. Moreover, NFTs can reshape the way industries operate by providing superior transparency, asset management, and intellectual property protection. This paper explores the potential of different types of NFTs, including dynamic and composable NFTs, in various applications within the industrial metaverse that heavily relies on digital twins. We present various industrial use cases where NFTs play a major role. Specifically, we design, implement, and test two use cases involving dynamic and composable NFTs. The data processing methods include algorithm development, simulation, and empirical testing within the industrial metaverse framework. Finally, we identify open research areas and future directions for the industrial metaverse.

Edisa Koro

This chapter looks at the interaction of decentralized finance and artificial intelligence in the financial industry. The investigation begins with a review of the history and objectives, laying the groundwork for a thorough study. Section 2 goes into the foundations of DeFi, addressing key ideas and ecosystem components necessary for understanding how it works. Following that, Section 3 explores AI's revolutionary potential in finance, focusing on its role in financial services and the many AI technologies driving industry innovation. Section 4 focuses on real-world applications, emphasizing use cases such as automated trading algorithms, risk management, fraud detection, and decentralized oracle networks to demonstrate the practical ramifications of merging DeFi with AI. Section 5 then discusses the issues and considerations that come with this paradigm change, such as ethical and regulatory concerns, as well as security threats related with decentralized technology and AI-powered systems. Finally, Section 6 provides a forward-looking view by highlighting themes that will impact the future.

Ankur Gupta, Surbhi Gupta, Saurabh Sharma

Decentralized Finance (DeFi) is expected to be the backbone for the metaverse facilitating B2B, B2C, and C2C commerce at scale. Blockchain and smart contracts are key drivers of the DeFi vision, enabling secure and non-repudiable financial transactions based on the fulfillment of pre-defined conditions. However, smart contract business logic can be faulty resulting in erroneous transactions and loss of capital. Testing smart contracts and ensuring 100% correctness also remains a challenge. Finally, to realize the interoperability requirement of the metaverse as mandated by the Metaverse Standards Forum (MSF), service providers shall be required to quickly scale and provide similar services across a plethora of metaverse platforms and ecosystems. Service providers also need to ensure the high availability of their DeFi services and remain resilient in the face of attacks. This research paper presents A Digital Twin Framework for smart contract-based applications for the metaverse, allowing DeFi service providers to create and maintain multiple active and passive twins of their services across metaverse platforms. Passive twins of the service can be used by prospective partners to test their smart contract execution and validate the outcomes. Passive twins can be activated dynamically to improve availability, ensure hyper-scaleup, or respond to attacks. Simulation results establish the effectiveness of the proposed framework laying the foundation for meeting the expectations for the future metaverse.

Shubhani Aggarwal, Neeraj Kumar, Amritpal Singh, Gagangeet Singh Aujla

Digital twins function as digital replicas of physical entities and play a pivotal role as facilitators in the digital world. They establish and foster the communication bridge between the physical and digital realms. Conversely, the metaverse represents an extension of digital twins, recognized as the 3D evolution of the Internet. These technologies aim to narrow the divide between the digital domain and human interaction, garnering considerable attention from academia and industry. Despite the metaverse predating digital twins by a decade, it remains in its emerging stages. In contrast, digital twins have found extensive applications across diverse fields. However, they are plagued by numerous security and privacy vulnerabilities that demand resolution for future communications. Therefore, leveraging the immutability and transparency inherent in blockchain, we have implemented these features into digital twins within the metaverse to enhance security and privacy. Consequently, a blockchain-empowered framework for the metaverse utilizing digital twins has been outlined. Furthermore, we have showcased the diverse applications of digital twins in the metaverse across various sectors. We have also designed a supply chain digital twins use-case scenario within the metaverse. The conceptual design and implementation details for the supply chain use case are discussed, focusing on traceability and data immutability. The proposed supply chain scenario is validated concerning various computational metrics. Finally, research trajectories concerning blockchain-based digital twins in the metaverse have been explored.

Chiara Colamartino, Francesco Manta, Pierluigi Toma

Certified products in agri-food are characterized by high quality and a strong territorial connection. This work explores the possible creation of Non-Fungible Tokens (NFT) for certified products in agri-food, due to the uniqueness and the artwork dimension attached to the product they identify. Questionnaires were submitted to explore the knowledge of NFTs and the propensity to purchase NFTs for certified agri-food products. We employ a proper Partial Least Square Structural Equation Modelling (PLS-SEM) and verify the predictive accuracy with the Artificial Neural Network (ANN) approach. The adequate receptivity of these technologies to the public is demonstrated and it is emphasized how Agriculture 4.0 can adapt NFT for certified products to enhance local development and increase the knowledge and blockchain system behind certified products. Direct implications include the potential for reinvestment in the activities of agri-food companies and consortia by positioning in the virtual space. Future research could focus on testing pilot projects and verifying the results of this preliminary study.

Zhanxue Wang, Lei Yu, Li Zhou

No abstract is available for this record.

Seyed Mohammad Mahdi Hamidi, Seyed Farzad Hoseini, Hadi Gholami, Mohammad Kananizadeh-Bahmani

No abstract is available for this record.

Stasia Stas, Sepehr Abrishami

Purpose In the current era of technological advancement, the architectural, engineering and construction (AEC) industry is undergoing a radical transformation, prompting researchers to explore new breakthroughs that can revolutionise the construction process. This paper delves into the use of cutting-edge technologies such as building information management (BIM), blockchain and the Internet of Things (IoT), along with advanced management techniques such as work breakdown structure (WBS) and Agile thinking, to enhance the industry’s efficiency, productivity, quality and cost-effectiveness. Moreover, the pressing need for a sustainable, secure and transparent sector amplifies the significance of the proposed research. Design/methodology/approach This study’s research approach comprises an intensive literature review to construct a conceptual framework, followed by an exploratory questionnaire to validate the framework. Findings This paper demonstrates how blockchain combined with a WBS and a BIM platform may boost collaboration in order to experience efficient and trusted workflow scenarios that can overcome many of the challenges given in a traditional building technique. The research findings emphasise the benefits of the proposed new mentality approach, which incorporates all of the previously described tools/techniques to the business. Research limitations/implications This paper highlights the advantages of leveraging a combination of blockchain, WBS and BIM platforms to boost collaboration and enable efficient and trustworthy workflow scenarios that can surmount the difficulties inherent in traditional AEC industry collaboration methods. Originality/value This study provides original insights into the challenges and opportunities of using blockchain for AEC collaboration, by exploring the potential of decentralised blockchain networks to improve the security, efficiency and transparency of collaborative data sharing and management.

Bilge Gokhan Çelik, Yewande S. Abraham, Mohsen Attaran

The emergence of construction 5.0 marks a shift toward a human-centric approach to digitization within the construction industry. Along with diverse digital innovations related to this shift, blockchain technology offers vast opportunities for the construction industry, including streamlining project management processes, enhancing transparency in payment processes, and improving contract administration. This paper systematically reviews 109 articles using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to examine the applications of blockchain in construction, identifying twenty-three topics across eight thematic areas. These areas were further mapped using VOSviewer Online version 1.2.3 to identify interrelationships among the themes and highlight their broad impact. Key features like immutability, security, transparency, and traceability show promise in contract administration, supply chain logistics, facilities management, and sustainability. However, the study also describes the challenges of adopting blockchain in construction, emphasizing the need for enhanced stakeholder education, improved regulatory frameworks, and the creation of industry-specific blockchain platforms to support its acceptance in the construction industry. Emphasizing emerging blockchain applications and the adoption challenges equips researchers and practitioners with the knowledge of these applications and their significance to construction practices.

Mohammadreza Najafzadeh, Hamidreza Abbasianjahromi, Seyedsoroush Zomorodi

Contract management, which directly impacts the success of architecture, engineering, and construction (AEC) projects, has been affected by the application of Industry 4.0 (I4.0) technologies. This study extensively reviewed the I4.0 application in contract management using a hybrid approach of bibliometrics and a systematic literature review to capture this trend. Scopus and Web of Science were selected as the papers’ databases, and 203 papers were filtered from a total of 2,524 papers from 2011 until the end of 2022. The bibliometric analysis explored and analyzed large volumes of data in six areas: publication year, journal, country, author, methodology, and keyword. The systematic literature review discovered eight key topics regarding I4.0 application and implication areas in the contract management of the AEC industry, including tender/bid phase, cost estimation, BIM contractual requirements, smart contracts, analyzing and monitoring contracts, claim and dispute management, information management and traceability, intellectual property rights; and regarding each topic, relevant I4.0 technologies were identified. Finally, benefits, challenges, and gaps of the literature were identified based on systematic analysis results. This paper contributes to the body of knowledge by identifying and synthesizing the current status of the research subject, and providing the researchers with the study’s theoretical and practical contributions.

Jiewu Leng, J F Guo, Dewen Wang, Yuanwei Zhong · 10 authors

Social manufacturing leverages the power of social networks and collaborative processes to enhance manufacturing capabilities and supports the sharing of ideas, resources, and information. However, traditional remote maintenance under a social manufacturing context lacks resilience against disruptions and cyber attacks. These issues often lead to interruptions in production. This article proposed blockchain-of-things-based edge learning contracts for federated predictive maintenance (FPM). First, given the diversity and heterogeneity of equipment, an open platform communication unified architecture (OPCUA)-based equipment meta-model is proposed to facilitate the interconnection and data sharing. Second, a Blockchain-of-Things-based secure access control approach is proposed, to directly collect data from controllers. This approach prevents tampering, unlike traditional local database collection methods. Third, to address the security and efficiency needs, an edge learning contract method is proposed for FPM. An integrated learning algorithm based on smart contracts is designed to achieve prediction performance that is comparable to local centralized training while reducing data transmission load and enhancing data security. Finally, a federated predictive maintenance platform is designed and implemented to enhance the system’s resilience, and its effectiveness is verified through case studies.

Yetong Wang, Kongduo Xing, Bing Zheng

Blockchain technology (BT) has been widely applied in the field of property rights transactions, especially when used as a distributed ledger for transaction data storage. This technology can effectively solve the problem of distrust among market entities. Distributed ledger, as a system architecture for distributed data management, maintains data records among multiple nodes through consensus mechanisms, ensuring that relevant information such as data ownership, propagation process, and transaction chain are fully and comprehensively recorded in the distributed ledger. Throughout the entire life cycle of data generation and flow, distributed ledgers ensure the immutability and non repudiation of data, providing strong support for rights confirmation, protection, and auditing. This article designs a distributed ledger and consistency maintenance algorithm for property rights digitization, aiming to explore how to ensure the immutability and non repudiation of data. The experimental results show that the algorithm can ensure the consistency of ledger data and effectively prevent data from being tampered with or denied. In high concurrency and large-scale data processing scenarios, algorithms can still maintain efficient and stable performance, providing reliable technical support for property rights transactions.

Diego Segura Ibarra, Fan Li, Jianjun Zhu, Jinyuan Chen

No abstract is available for this record.

Kesava Rao Alla, Gunasekar Thangarasu

Food supply chain (FSC) is an important part of the food supply chain. It is essential to establish food supply chains that are open to the public, accountable for their actions, and available in real time. The development of blockchain technology has led to an increase in the amount of data that is passed between customers and businesses, as well as the data that are passed between them. Blockchain technology is a new type of information technology that has the ability to be decentralized, safe, and trusted, which makes it an excellent option for storing sensitive data. The purpose of this study is to evaluate how blockchain with deep learning is used to find the quality evaluation of food supply chain technology. The use of BC has improved the accuracy of food traceability, while the utilization of Deep Random Forest (DRF) has boosted the efficacy of computing and shortened the reaction time. The research compares the quality evaluation system that is based on BC-DRF with some of the most common existing methods in terms of accuracy, reaction time, and sensitivity, when applied to a variety of block sizes.