A digital twin is a virtual software system that simulates the workings of an actual object or process. The majority of digital twin information is centralized and does not adequately support data management security, integrity maintenance, or trustworthiness and precision of timeconsuming processes. It is imperative that blockchain be integrated with digital twins to address these restrictions. With blockchains, digital twin data can be shared across secured connection systems with confidence in terms of both accuracy and transmission speed. Blocks of data that track network transactions make up blockchains. These blockchains are maintained on distributed ledgers and are incorporated into the chain as new blocks. Several open-source frameworks of Blockchain such as Hyperledger Fabric, Ethereum, Corda, Quorum, Solidity, Geth, Remix, Mist, Solium, Truffle, Parity, DApp Board, Embark, MyEtherWallet, etc., were explored. Digital Twin open-source tools such as Ansys Digital Twin 92 Builder, Ditto, Kafka, AWS Digital Twin, AWS IoT TwinMaker, Twinbase, etc., were discussed. Also, various open-source platforms such as Dovetail, EtherTwin, SmartTwin, Remix, Solidity, TIBCO Cloud™ Live Apps, Watson IoT Platform, etc., for building Blockchain-based Digital Twin frameworks were discussed. The chapter discusses the conceptual framework of blockchain-based digital twin and its significance in the industry sector. It explores the various open-source platforms for implementing blockchain-based digital twins. This chapter will be useful for researchers, academicians, and industry practitioners to understand the amalgamation of blockchain-based digital twins.
Innocent B. Ababio, Jan Bieniek, Mohamed Rahouti, Thaier Hayajneh · 7 authors
Optimizing digital twins in the Industrial Internet of Things (IIoT) requires secure and adaptable AI models. The IIoT enables digital twins, virtual replicas of physical assets, to improve real-time decision-making, but challenges remain in trust, data security, and model accuracy. This paper presents a novel framework combining blockchain technology and federated learning (FL) to address these issues. By deploying AI models on edge devices and using FL, data privacy is maintained while enabling collaboration across industrial assets. Blockchain ensures secure data management and transparency, while explainable AI (XAI) enhances interpretability. The framework improves transparency, control, security, privacy, and scalability for self-optimizing digital twins in IIoT. A real-world evaluation demonstrates the framework’s effectiveness in enhancing security, explainability, and optimization, offering improved efficiency and reliability for industrial operations.
Amit Kumar Sharma, L. Ganesh Babu, Mrunalini Buradkar, M. Shanmathi · 6 authors
PURPOSE: With a focus on enhancing transparency, lowering the risk of fraud, and ensuring ethical sourcing practices, this research aims to investigate how blockchain and IoT technologies can be incorporated into the diamond supply chain. This study addresses the complexities and challenges of implementing these technologies in an industry characterized by fragmented information sharing and centralized data storage. DESIGN/METHODOLOGY/APPROACH: Using both qualitative and quantitative analysis, the research uses a mixed-methods approach. While secondary data was obtained from previously published works, industry reports, and case studies, primary data was gathered through semi-structured interviews with professionals in the field. The implementation of the prototype system was carried out in three phases: Define, Operate, and Test. Ethereum was chosen for its smart contract capabilities, and various IoT sensors were deployed to monitor environmental conditions and track the real-time location of diamonds. FINDINGS: The integration of blockchain and IoT technologies significantly enhanced transparency within the diamond supply chain. The immutable nature of blockchain ensured tamper-proof records of transactions, while IoT sensors provided continuous real-time data, reinforcing transparency. The study observed a notable reduction in fraud due to the robust mechanisms of the system, which detected and prevented unauthorized alterations to the recorded data. Smart contracts automated compliance checks, ensuring adherence to ethical standards. Quantitative analysis revealed improvements in key metrics such as fraud reduction rates, transparency enhancements, and adherence to ethical sourcing standards. ORIGINALITY/VALUE: This study bridges a notable gap in existing research by focusing on the diamond supply chain. It provides comprehensive, data-driven insights and practical recommendations for industry stakeholders and policymakers. The results highlight how combining blockchain and IoT technology can improve operational efficiency, transparency, and ethical practices in the diamond business. It is also feasible and scalable. The study's methods and findings add a great deal to the body of information already in existence and provide a framework for further investigation and application in related situations.
• First comprehensive review of ML models for end-of-life product return predictions. • Integration of PRISMA systematic review with network and meta -analysis methods. • Key factors influencing ML prediction accuracy in reverse supply chains. • Six future research directions for AI-enhanced circular-economy logistics. The evolution of the circular economy has led to the adoption of circular supply chains, where efficient management of the reverse supply chain enhances resource utilization, minimizes waste, and fosters a circular supply chain. However, managing reverse supply chains presents numerous challenges including a lack of information transparency and traceability, inconsistent cooperation among stakeholders, and uncertainty in recycling process, such as variations in quantity, quality, and timing. To address these challenges, an information sharing framework that integrates blockchain technology with digital product passports (DPPs) is designed to manage reverse supply chain information. Subsequently, a system dynamics model is applied to evaluate the potential impacts and feasibility of this framework within the reverse supply chain and its implications for the forward supply chain. The results indicate that the application of the proposed framework enhance the legal recycling market, reduces the negative environmental impact of illegal recycling activities, mitigates the bullwhip effect within the forward supply chain, and improves market fulfillment rate. The proposed information sharing framework can be employed to enhance the information efficiency of the reverse supply chain, aid in the recovery of end-of-life products and critical resources utilization, thereby supporting the transition to a circular economy.
This paper addresses critical food safety challenges in modern agricultural supply chain management by proposing an AI-driven quality chain system design. The system integrates five key chains—agricultural product quality, capital flow, logistics, and accountability—into a unified accounting information framework through artificial intelligence and multidimensional accounting theories, achieving "five-chain integration". Centered on "quality accountability", the intelligent open, decentralized, and industry-finance integrated agricultural supply chain management system enhances transparency, traceability, precision, and collaboration within the sector. It plays a vital role in establishing fair market competition, guiding industrial cycles, optimizing resource allocation, and building market confidence while reinforcing social responsibility.
J. Thimmia Raja, Ashish Ashish, Sindhu Boianapalli, Soma Sabitha M · 6 authors
Blockchain technology, as a growing innovation, offers a viable solution to enhance transparency, traceability, and efficiency in global supply chains. While blockchain has great potential, several challenges remain, including scalability, integration with legacy systems, standardization, energy consumption, privacy concerns, and regulatory uncertainty. This enrollment of data is hoped to tackle these problems of dilemmas, whislt subsequent improved effective equates being more reasonable in terms of deploying blockchain applications. With the goal of offering a bridge to most projects still unsure whether to adopt Blockchain technology or to continue under what we call "Blockchain in the cloud" approach, this study introduces effective solutions on how to integrate Blockchain with current systems through innovative hybrid systems, standardized user protocols, and new consensus protocols that optimize cost of implementation and environmental impact. The other aspect of the research undertakes to design clear regulatory frameworks and change management systems that can aid in the adoption of blockchain technology for traditional supply chain stakeholders. By utilizing real-world case studies and the simplification of smart contract deployment, this work illustrates the practical benefits blockchain can provide in enhancing supply chain operations. In conclusion, the goal of this study is to pioneer a sustainable, secure, and efficient blockchain ecosystem that promotes trust, transparency, and collaboration among supply chain partners, ensuring the future viability of the technology.
Yahaya Saidu, Shuhaida Mohamed Shuhidan, Izzatdin Abdul Aziz, Md. Mahmudul Alam · 7 authors
The integration of Blockchain (BC) and the Internet of Things (IoT) has emerged as a transformative solution for addressing traceability challenges in logistics, offering enhanced transparency, data security, and operational efficiency. This study presents a systematic review of the current state of BC-IoT integration for logistics traceability, focusing on its motivations, deployment strategies, technical implementations, and evaluation approaches. A total of 1,619 records were initially retrieved from IEEE Xplore, MDPI, ScienceDirect, Scopus, and Web of Science, from which 61 peer-reviewed studies published between 2015 and 2024 were selected and analyzed. The selection process adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure a rigorous, transparent, and high-quality synthesis. Only studies explicitly addressing the convergence of BC and IoT within logistics traceability contexts were included. Key findings reveal that BC-IoT systems significantly enhance traceability and transparency across logistics networks but face persistent challenges such as scalability, latency, energy efficiency, and security. The review categorizes various deployment architectures including cloud, edge, fog, and hybrid models, and examines their implications for data responsiveness and system reliability. Additionally, it evaluates popular BC platforms (e.g., Hyperledger Fabric, Ethereum, Solana) and consensus mechanisms (e.g., RAFT, PBFT, PoS) based on their suitability for logistics applications. Emerging research directions emphasize the need for cross-chain interoperability, domain-specific frameworks, and decentralized traceability models, particularly in sectors such as humanitarian logistics and regulatory compliance. This review consolidates fragmented knowledge and provides actionable insights for developing scalable, secure, and transparent BC-IoT systems to support next-generation logistics operations.
Das Baumanagement steht aufgrund ineffizienter Zusammenarbeit, fragmentierter Abläufe und uneinheitlicher Dokumentation vor großen Herausforderungen. Diese Probleme behindern Vertragsverwaltung, Prozessverfolgung und Datenaustausch und führen oft zu Streitigkeiten, Verzögerungen und Kostenüberschreitungen. Blockchain-basierte Smart Contracts bieten Potenzial für Automatisierung, Transparenz und Sicherheit, werden jedoch bisher nur unzureichend genutzt und in BIM integriert, um branchenspezifische Anforderungen zu erfüllen. Diese Arbeit untersucht, wie Smart Contracts das digitale Baumanagement verbessern können - mit Fokus auf BIM-Datennutzung, automatischer Vorlagenerzeugung, Prozessüberwachung und Systemintegration. Die Lösung umfasst drei Verfahren: Datenmodellierung, Prozessvorlagendefinition und Smart-Contract-Implementierung. Validiert durch drei Anwendungsfälle und entwickelte Prototypen legt sie die Grundlage für ein zuverlässigeres und stärker kollaborativeres Baumanagement.
Industrial Cyber-Physical Systems (ICPSs) play a vital role in modern industries by providing an intellectual foundation for automated operations. With the increasing integration of information-driven processes, ensuring the ... | Find, read and cite all the research you need on Tech Science Press
Chiara Bartoli, Francesco Fasano, Francesco Cappa, Paolo Boccardelli
This paper examines the role that the metaverse and non-fungible tokens (NFTs) play in innovating the business model of firms. We employed qualitative data collected through a survey, which included more than 100 managers at both small and medium-sized enterprises and large enterprises representing over 20 different industrial sectors, and through a panel of experts. The empirical outcomes show that the metaverse and NFTs can be significantly leveraged by firms to innovate the building blocks of their business models in different ways, as summarized in the framework we have developed, which provides a guide to best practices when adopting these emerging technologies. In addition, this work also highlights the major challenges faced in the adoption of such technologies. In doing so, our aim is to advance overall scientific understanding of the metaverse and NFTs, which facilitates conscious implementation, and to highlight the potential for innovation that should be considered to favour business development.
Lean Six Sigma 4.0 (LSS 4.0) represents a transformative evolution of Lean Six Sigma, integrating Industry 4.0 technologies to drive smart manufacturing excellence. By leveraging Artificial Intelligence (AI), the Internet of Things (IoT), Digital Twins, and Big Data Analytics, LSS 4.0 enables realtime decision-making, predictive intelligence, and autonomous process optimization, enhancing efficiency, agility, and resilience in modern industrial environments. This paper introduces a conceptual framework for LSS 4.0, redefining the DMAIC (Define-Measure-Analyze-Improve-Control) methodology through IoT-driven process monitoring, AI-powered predictive analytics, and digital twin simulations. This transformation shifts manufacturing from reactive control to predictive and autonomous optimization, reducing variability, defects, and waste while maximizing productivity, resource efficiency, and sustainability. By leveraging data-driven decision-making, intelligent automation, and predictive maintenance, the framework enhances process reliability, prevents defects, and improves operational performance. Despite its advantages, LSS 4.0 presents challenges, including technological complexity, workforce upskilling, and organizational resistance. This study underscores the critical role of leadership-driven digital transformation, AI-augmented decision-making, and targeted skill development in fostering an innovation-driven manufacturing culture. Additionally, blockchain for secure supply chain traceability, augmented reality (AR) for enhanced humanmachine collaboration, and edge computing for decentralized intelligence are explored as key enablers of LSS 4.0’s full potential. Leadership commitment, cross-functional collaboration, and AI-driven Lean workflows are identified as essential success factors. Aligning digital transformation strategies with Lean principles and fostering a culture of continuous innovation is crucial for realizing LSS 4.0’s full benefits. Finally, this study highlights future research directions, emphasizing Industry 5.0 advancements such as human-centric automation, collaborative robotics, and sustainable smart manufacturing—key drivers in building adaptive, intelligent, and resilient industrial ecosystems.
Cyber-Physical-Social Systems (CPSS), as emerging paradigms, are evolving to address the growing need for intelligent, adaptive, and transparent decision-making in complex environments such as smart cities and industrial systems. However, the advancements enabled by Digital Twins (DTs), centralized governance models, and opaque analytics limit scalability and resilience. In this study, we propose a decentralized governance framework that integrates Decentralized Autonomous Organizations (DAOs) and blockchain-based predictive analytics to enhance trust, interoperability, and ethical decision-making for CPSS. The proposed framework utilizes immutable ledgers, automated smart contracts, and community-driven governance to improve real-time collaboration, thereby ensuring system resilience and facilitating adaptive optimization. The remarkable innovation of the CPSS framework lies in combining digital tokens (DTs) within a blockchain application. We believe that our approach provides a scalable mechanism for autonomous decision-making and secure data sharing across multi-stakeholder ecosystems. In this regard, using theoretical analysis and comparative evaluations, we have demonstrated how our framework mitigates conventional challenges in CPSS governance, including security vulnerabilities, algorithmic fairness, and data integrity. Moreover, this research makes a significant contribution to the advancement of decentralized digital twin (DT) infrastructures, paving the way for more robust, ethically aligned, and resilient cyber-physical systems.
Abstract In the rapidly evolving landscape of IoT-enabled smart devices, significant challenges persist in integration to web3, security, and data reliability. This research presents the design and integration of IoT assets, particularly devices, through the Novel Decentralized Smart City of Things (DSCoT) framework. ESP32 microcontrollers serve as Ethereum clients, generating Externally Owned Accounts (EOA) for device identification and authentication. Despite resource constraints, including limited computational capabilities, essential libraries that manage tasks such as Wi-Fi module control, interaction with Ethereum-based blockchains, TCP connection management, and EEPROM operations for persistent data storage. The code is structured with functions for Wi-Fi setup, TCP API requests, and secure communication challenges. Integration involves compiling and flashing the code onto ESP32 devices, verifying EOA generation, and mapping devices, fog nodes, and users through smart contract interactions. The deployment process culminates in the generation of Non-Fungible Tokens (NFTs) for user authentication, with transaction verification on the Goerli testnet confirming successful DSCoT edge system implementation. This research underscores the importance of secure and decentralized integration of IoT-enabled smart devices to the blockchain, enhancing performance while ensuring security and transparency.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security