Slow and disputed progress payments undermine contractor liquidity and project schedules due to manual verification, fragmented data, and limited transparency. This paper presents a prototype system that incrementally integrates digital twin (DT), building information modeling (BIM), and blockchain to automate milestone-based payments. The continuously updated DT is conceptualized as a dynamic oracle, capturing real-time site conditions and comparing them with structured BIM milestones. Verified achievements trigger Ethereum smart contracts referencing Merkle-proofed evidence stored off-chain in InterPlanetary File System (IPFS), with disbursements authorized via Gnosis Safe multi-signature wallets. A prototype on a police station project shortened verification to payment from several days to minutes and eliminated disputes across all milestones. A survey of industry professionals confirmed gains in efficiency, transparency, and trust. The proposed system provides a practical foundation for transparent, automated payments and offers pathways for future adoption such as stablecoin settlement and public sector integration. ⢠Digital twins resolve blockchain oracle challenges in construction payments. ⢠BIM-blockchain integration reduces payment verification from days to minutes. ⢠Smart contracts with multi-signature governance secure transaction integrity. ⢠Stakeholders confirm enhanced payment speed, transparency, and trust.
This paper addresses the application of blockchain in Digital Twin (DT) systems, which often rely on centralized architectures, by proposing and evaluating a decentralized management system for vehicle DTs. The system uses Ethereumbased ERC-1155 NFTs to represent vehicles. Smart contracts handle NFT minting, ownership transfers, and a three-phase lifecycle. Off-chain data is stored on IPFS, with privacy secured by an algorithm based on ECDH. A decentralized application was developed to enable interaction with the blockchain and IPFS. Evaluation of the system included static analysis, automated testing, and gas cost analysis. The system is capable of managing a vehicle NFT from its inception until its decommissioning, with all actions recorded on the blockchain and IPFS. While scalable at the smart contract level, Ethereumâs network throughput can pose limitations for full-scale automotive industry adoption, suggesting suitability for smaller-scale applications or the necessity for improvements in both Layer 1 and Layer 2 solutions. This work demonstrates a feasible end-to-end Web3 solution for vehicle Digital Twins, bringing transparency and data integrity to the vehicular ecosystem.
La tesi esplora il fenomeno della trasformazione digitale, evidenziandone lâevoluzione storica, le tecnologie abilitanti e i benefici strategici per le imprese lungo dimensioni operative, decisionali, innovative e di customer experience. La trasformazione digitale viene presentata come un processo sistemico che coinvolge la digitizzazione, digitalizzazione e infine una profonda ridefinizione dei modelli di business, delle strutture organizzative e delle strategie competitive. Particolare attenzione è dedicata alla tecnologia blockchain, analizzata nei suoi aspetti tecnici fondamentali (nodi, transazioni, blocchi, meccanismi di consenso come Proof of Work e Proof of Stake) e alle sue caratteristiche distintive di sicurezza, immutabilitĂ e decentralizzazione, che la rendono idonea a supportare nuovi paradigmi economici e istituzionali. La tesi approfondisce lâimpatto organizzativo della blockchain, con focus sulla digitalizzazione dei processi aziendali, la ridefinizione della divisione del lavoro e i nuovi assetti regolativi e di coordinamento. Si analizzano le Decentralized Autonomous Organizations (DAO) come forme emergenti di organizzazione digitale, fondate su regole programmabili e governance distribuita, che sfidano i modelli tradizionali introducendo automatismi decisionali e nuovi criteri di fiducia. Vengono inoltre discussi i benefici e le sfide connesse allâadozione della blockchain e delle DAO, incluse questioni di scalabilitĂ tecnica, interoperabilitĂ , sicurezza e incertezze normative, ponendo lâaccento sulla necessitĂ di integrare competenze tecnologiche, giuridiche e organizzative per sfruttarne appieno il potenziale trasformativo. La tesi presenta la blockchain come infrastruttura digitale generativa capace di abilitare modelli innovativi di collaborazione e governance, con profonde implicazioni per la competitivitĂ e la resilienza organizzativa in un contesto economico sempre piĂš digitalizzato e distribuito.
Murugan Ramu, Sneha T, Hemalakshmi V B, K Shwetha ¡ 6 authors
Enterprise Resource Planning (ERP) systems are pivotal in managing organizational workflows across departments such as finance, human resources, inventory, and procurement. However, traditional ERP systems are prone to inefficiencies including lack of transparency, delayed approvals, data inconsistencies, and audit complexities. This paper introduces ChainAutomate-ERP, a blockchain-powered workflow automation framework that integrates smart contracts, reinforcement learning (A3C) agents, and IPFS-based document storage to enhance ERP operations. The proposed SmartFlowChain-Net architecture ensures tamper-proof workflow execution, decentralized approvals, and AI-driven optimization of task routing and resource utilization. A permissioned blockchain network using Hyperledger Fabric is configured with department-wise node identities and inter-channel communication for secure data exchange. Smart contracts autonomously govern workflows such as invoice processing, purchase orders, and leave approvals, eliminating human error and procedural delays. Reinforcement learning agents trained with historical data significantly improved resource allocation and decision efficiency. The framework was benchmarked against traditional ERP systems across five key performance dimensions. Experimental results demonstrate substantial improvements: average workflow execution time reduced by 58.6%, approval accuracy increased from 88.1% (manual) to 98.2% (blockchain-based), and resource allocation efficiency rose from 69.4% to 91.5%. Moreover, audit time dropped by 63.7%, and integrity check failures per 1000 transactions decreased by over 90%. The findings confirm that ChainAutomate-ERP delivers a secure, transparent, and scalable automation layer for next-generation ERP ecosystems. The integration of AI and blockchain technologies positions the system as a transformative solution for enterprises seeking operational excellence and regulatory compliance.
This paper explores the integration of Blockchain technology into Structural Health Monitoring (SHM) to enhance data traceability, integrity, and automation in infrastructure asset management. Traditional SHM approaches, including Digital Twin-based systems, often face limitations related to data tampering, sensor unreliability, and the lack of transparent and verifiable data workflows. To address these challenges, the SHERPA framework is proposed. SHERPA leverages decentralized storage via the InterPlanetary File System and three Smart Contracts dedicated to data validation, anomaly flagging, and automated workflow execution. Rather than focusing on the structural interpretation of data, SHERPA establishes a secure and auditable backbone for SHM data governance. A prototype implementation on the Canalone Viaduct in Italy demonstrated the feasibility of the system, showcasing automated response to threshold violations and immutable data registration. The framework proved effective in enhancing transparency, traceability, and stakeholder confidence, positioning SHERPA as a promising enabler of more trustworthy and accountable SHM systems.
AndrĂŠs FernĂĄndezâMiguel, Susana OrtĂz-Marcos, Mariano JimĂŠnez, Alfonso Pedro FernĂĄndez del Hoyo ¡ 6 authors
This study advances toward establishing the theoretical foundations of Industry 6.0 by developing a comprehensive framework that integrates artificial intelligence (AI), decentralized control systems, and cyberâphysical production environments for intelligent, sustainable, and adaptive manufacturing. The research employs a tri-modal methodology (deductive, inductive, and abductive reasoning) to construct a theoretical architecture grounded in five interdependent constructs: advanced technology integration, decentralized organizational structures, mass customization and sustainability strategies, cultural transformation, and innovation enhancement. Unlike prior conceptualizations of Industry 6.0, the proposed framework explicitly emphasizes the cyclical feedback between innovation and organizational design, as well as the role of cultural transformation as a binding element across technological, organizational, and strategic domains. The resulting framework demonstrates that AI-driven decentralized control systems constitute the cornerstone of Industry 6.0, enabling autonomous real-time decision-making, predictive zero-defect manufacturing, and strategic organizational agility through distributed intelligent control architectures. This work contributes foundational theory and actionable guidance for transitioning from centralized control paradigms to AI-driven distributed intelligent manufacturing control systems, establishing a conceptual foundation for the emerging Industry 6.0 paradigm.
Industry 5.0 is a hot topic in the current technological business scenario. Industry 4.0 has not reached its full potential as of now, and Industry 5.0 can help Industry 4.0 to target a 100% adoption rate by using it as a base and inculcating human centricity, better traceability, enhanced transparency, better coordination, and sustainability. Industry 5.0 is a far more, holistic approach and it has a wider scope in associating with upcoming technologies such as-6G (for faster, safer, and more stable real-time communication); Decentralized Autonomous Organization enhances the capabilities of decision-making, and also supports decentralized decision-making at the time of crisis; and Parallel Intelligence increases safety as well as capability to have self-healing systems and enhanced human centricity. This paper tries to explain various components of Industry 5.0. Additionally, it aims to fill the gap in the literature and effectively provide future research directions, with an emphasis on the interplay between the components of Industry 5.0, rating systems for Industry 5.0, and the broader Industry 5.0 ecosystem and governance. This paper uses data from ScienceDirect, IEEE Xplore, and Google Scholar databases. We conclude this study by suggesting the need for more empirical research in this domain.
Consortium blockchains (e.g., Hyperledger Fabric) have been adopted for inter-organizational supply chain management, while NFTs have gained attention to represent asset uniqueness and ownership on public blockchains (e.g., Ethereum). Applying NFTs to supply chains offers the potential to track individual products and enable seamless lifecycle management, including consumer engagement. Also, standardized smart contract interfaces for NFTs (e.g., ERC721) promote interoperability across blockchain services. However, traditional NFTs are limited to single-asset representation and lack features needed for enterprise use, such as support for composite products, access control, and efficient ledger storage. Recognizing the potential of ERC-7401 (nested NFTs) for enabling hierarchical NFT structures, this study investigates its application to traceability in consortium-based supply chains. We designed a nested NFT framework on Hyperledger Fabric, incorporating attribute-based access control and block size reduction mechanisms through transient arguments and batch processing. We implemented a prototype on Hyperledger Fabric that integrates block size reduction and access control mechanisms into Nested NFTs. Through design and implementation, we demonstrated the feasibility of this approach for complex supply chain management.
Predictive maintenance in cross-border unmanned logistics systems (CBULS) faces persistent challenges, including data privacy, system heterogeneity, and collaborative efficiency. Existing studies that combine federated learning with blockchain address only partial aspectsâsuch as communication or trustâbut fail to effectively handle non-independent and identically distributed (non-IID) data, integrate multi-layer privacy, or design consensus mechanisms tailored to cross-border logistics. This paper proposes a predictive maintenance framework that integrates an improved FedProx algorithm with a hybrid Delegated Proof of Stake (DPoS) and Practical Byzantine Fault Tolerance (PBFT) consensus. The framework incorporates zero-knowledge proofs, fully homomorphic encryption, and local differential privacy, while employing hierarchical architecture and sharding for scalability. Simulation results show that the proposed method improves prediction accuracy by 6.9% compared with FedAvg and 3.7% compared with FedProx, enhances privacy protection by over 12%, increases system throughput by approximately 23%, and reduces transaction confirmation latency by nearly 18%. These results demonstrate that the framework provides a secure, efficient, and scalable solution for predictive maintenance in CBULS.
The major challenges faced by confectionery supply chain are lack of information, traceability, managing the ownership of goods across supply chains, inability to track vendors in real-time. Blockchain and Internet of Things (IoT) in Industry 4.0 era help organisations to overcome these challenges by guaranteeing authentic information, real-time visibility, and transparency across the supply chain management. The extant literature has revealed that blockchain and IoT technologies are in their early stages of information management for the supply chain. This study explores the potential opportunities available with Blockchain and IoT in the confectionery supply chain. Utilising the inputs from the survey and interviews, the article identifies to present the gaps in the supply chain and proposes a new blockchain and IoT-based architecture of the food safety system for the confectionery supply chain. Typical blockchain architecture is designed for a food safety system, and the technical specifications required to implement blockchain are evaluated. Further, blockchain-assisted distribution information management is proposed to bring more visibility to the shipment of goods. Implications of deploying blockchain and IoT in the supply chain from a management perspective are discussed. The study distinguishes itself from existing literature in two ways: first, by introducing a tailored blockchain and IoT architecture specifically designed for food safety in the confectionery supply chain; and second, by demonstrating its practical implications in addressing real-time traceability, transparency, and operational efficiency in line with Industry 4.0 goals. This integrated approach helps organisations make informed decisions, reduce supply chain risks, and improve regulatory compliance across the confectionery value chain.
The integration of distributed digital twins (DTs) within an industrial metaverse presents a significant challenge to system stability and predictability. Continuous, asynchronous updates to individual DTs and their underlying generative AI foundation models create dynamic interdependencies that traditional, centralized requirements management systems cannot adequately govern due to inherent issues of trust, transparency, and data integrity. This paper argues for a paradigm shift, proposing a decentralized, multi-party requirements management framework built on Web3 distributed ledger technology. In this approach, requirements are transformed from static documents into immutable, traceable transactions on a shared ledger, with their validation and enforcement automated through smart contracts. The proposed system establishes a single, verifiable source of truth, enabling the use of automated guardrails and negotiated adjustments to contain the impact of changes. This ensures that the complex mesh of DTs can co-evolve in a stable, predictable, and secure manner, addressing key barriers and fostering the adoption of a collaborative industrial metaverse, as illustrated through a practical semiconductor manufacturing use case.
The sustainable and efficient management of the built environment is a crucial challenge in the increasingly digitalized AEC sector. Innovative technologies such as Building Information Modeling (BIM) and Digital Twin (DT) offer significant opportunities to enhance the operational efficiency and sustainability of physical assets. However, digitalization generates vast amounts of Big Data, and their handling through centralized architectures leads to risks of fragmentation, lack of transparency, and vulnerability to manipulation. In response to these challenges, this study presents an innovative Proof of Concept (PoC) that integrates Blockchain (BT), Digital Twin (DT), and Non-Fungible Token (NFT) technologies to promote decentralized and sustainable data management in the construction industry. The application, called dDT (decentralized Digital Twin), was initially deployed on the Solana blockchain and later integrated with Polygon to leverage EVM compatibility and the ERC-721 standard for NFTs. The platform enables the tokenization of data flows generated by physical assets, ensuring traceability, security, and transparency throughout the entire asset lifecycle. The dDT system represents a sustainable innovation as it creates a secondary data market, fostering collaboration among industry stakeholders and financing new developments through the sale of data-linked NFTs. This decentralized solution addresses fragmentation and transparency issues, promoting more secure, resilient, and sustainable data management practices. The PoC demonstrates how the integration of BT, DT, and NFT can accelerate the transition toward more efficient and innovative practices, with positive impacts on sustainability and technological advancement in the AEC sector.
Rahanatu Suleiman, Akshita Maradapu Vera Venkata Sai, Wei Yu, Chenyu Wang
Digital Twins (DTs) have become essential tools for improving efficiency, security, and decision-making across various industries. DTs enable deeper insight and more informed decision-making through the creation of virtual replicas of physical entities. However, they face privacy and security risks due to their real-time connectivity, making them vulnerable to cyber attacks. These attacks can lead to data breaches, disrupt operations, and cause communication delays, undermining system reliability. To address these risks, integrating advanced security frameworks such as blockchain technology offers a promising solution. Blockchainsâ decentralized, tamper-resistant architecture enhances data integrity, transparency, and trust in DT environments. This paper examines security vulnerabilities associated with DTs and explores blockchain-based solutions to mitigate these challenges. A case study is presented involving how blockchain-based DTs can facilitate secure, decentralized data sharing between autonomous connected vehicles and traffic infrastructure. This integration supports real-time vehicle tracking, collision avoidance, and optimized traffic flow through secure data exchange between the DTs of vehicles and traffic lights. The study also reviews performance metrics for evaluating blockchain and DT systems and outlines future research directions. By highlighting the collaboration between blockchain and DTs, the paper proposes a pathway towards building more resilient, secure, and intelligent digital ecosystems for critical applications.
Linjing Liu, Yushi Chen, Jia Yang, ChengâFu Yang
Supply chain finance (SCF) plays a key role in easing financing difficulties for small and medium-sized enterprises, but it also comes with risks such as information asymmetry, fraud involving pledged assets, and delays in credit evaluation.In this study, we introduce a dynamic risk management framework driven by IoT and enhanced by the integration of multiple technologies.Built on a four-layer IoT structure, comprising perception, network, processing, and application layers, the framework combines blockchain for secure and trusted data sharing, federated learning for collaborative data processing, and digital twin models for real-time risk simulation.At the perception level, 5th-Generation Mobile Communication Technology (5G)enabled low-power sensors ensure comprehensive and tamper-proof data collection.The network layer uses blockchain techniques such as sharding and zero-knowledge proofs to safeguard data privacy and institutional trust.In the processing layer, federated learning combined with edge and cloud computing enhances credit evaluation.On the other hand, the application layer employs smart contracts and feedback mechanisms to enable real-time responses and adaptive risk strategies.To put this framework into practice, we propose a phased approach: first building a real-time data ecosystem, then deploying secure risk control systems, optimizing distributed computing, and finally integrating a closed-loop risk control mechanism.This modular, collaborative strategy ensures that technological systems align with actual business needs.Ultimately, the research demonstrates how IoT, blockchain, and AI can work together to create a scalable and practical model for managing risk dynamically in SCF.
The Agentic Service Ecosystem consists of heterogeneous autonomous agents (e.g., intelligent machines, humans, and human-machine hybrid systems) that interact through resource exchange and service co-creation. These agents, with distinct behaviors and motivations, exhibit autonomous perception, reasoning, and action capabilities, which increase system complexity and make traditional linear analysis methods inadequate. Swarm intelligence, characterized by decentralization, self-organization, emergence, and dynamic adaptability, offers a novel theoretical lens and methodology for understanding and optimizing such ecosystems. However, current research, owing to fragmented perspectives and cross-ecosystem differences, fails to comprehensively capture the complexity of swarm-intelligence emergence in agentic contexts. The lack of a unified methodology further limits the depth and systematic treatment of the research. This paper proposes a framework for analyzing the emergence of swarm intelligence in Agentic Service Ecosystems, with three steps: measurement, analysis, and optimization, to reveal the cyclical mechanisms and quantitative criteria that foster emergence. By reviewing existing technologies, the paper analyzes their strengths and limitations, identifies unresolved challenges, and shows how this framework provides both theoretical support and actionable methods for real-world applications.
<ns3:p>The emergence of Web 3.0 and the Metaverse marks a transformative shift in the evolution of the internet and digital ecosystems. This paper explores the foundational principles of decentralization, user autonomy, and data transparency that underpin Web 3.0 technologies, including blockchain, smart contracts, and digital wallets. We analyze how these innovations are reshaping business models, enabling new forms of value creation, and redefining digital ownership and governance. In parallel, we examine the Metaverse as a virtual, immersive environment integrating Web 3.0 infrastructure, and its potential to revolutionize sectors such as logistics, education, finance, and data management. The study also highlights the critical role of a holistic framework encompassing technological, economic, and legal pillars. A special focus is given to data provenance, privacy-preserving computation, and the need for coherent regulatory strategies in light of GDPR, the AI Act, and the Data Act (European Parliament, 2016; European Parliament, 2023; European Parliament, 2024). Finally, we identify emerging challenges related to NFT authenticity, system sustainability, and user experience, proposing a multidisciplinary and lean governance approach to guide future developments.</ns3:p>
Heba Abdul-Jaleel Al-Asady, K. Priyanka, V. Vennila, M. Murali ¡ 5 authors
In modern supply chains, visibility and sustainability is becoming dependent on energy-efficient and auditable data management frameworks. The use of blockchainbased auditing methods can yield transparent visibility and mechanized auditing capabilities. However, typical auditing solutions using blockchain come with significant energy resource-consuming overheads that are not viable in Industrial IoT (IIoT). In contrast, traditional routing methods do not concurrently account for energy consumption at multiple layers of complexity. In this paper, a novel framework consisting of Fuzzy Logic-Based Energy Aware Routing (FLEA-RPL) combined with the lightweight Internet of Things Application (IOTA) Tangle is proposed, for green supply chain auditing. This is done by first collecting the sensor data (temperature, location, and, residual energy) from the IIoT nodes. The data is preprocessed to receive a similar distribution for incoming sensor data and to filter out inconsistent anomalies. Moreover, FLEA-RPL uses fuzzy inference to assess and choose optimal parent nodes to route the data to nodes on the routing tree, for minimizing energy consumption, according to residual energy and, load to send the data. The routed data is then permanently logged onto a Tangle so that the route is immutable and, therefore, low power and energy data is permanently attached to the distributed ledger. The final step is that the intelligent compliance auditing module monitors the contents of the distributed ledger for violations of a certain Service Level Agreement (SLA) from the ledger. The proposed FLEA-RPLIOTA attained better results, when compared FLEA-RPL in terms of Residual Energy (97.74 %), Packet Loss Ratio (2.2 %) respectively.
Ningshuang Zeng, Xuling Ye, Shiqi Chen, Yan Liu ¡ 6 authors
The integration of off-site manufacturing with onsite construction in the Modular Construction Supply Chain (MCSC) presents significant challenges due to the differences in production methods and geographical distances.While various technologies have transformed construction practices, substantial improvements are still needed in on-and off-site coordination to mitigate delays, ensure quality, and lower costs.Blockchain-enabled smart contracts offer a promising workflow engine for enhancing processoriented MCSC coordination.Additionally, Robotic Process Automation (RPA) holds the potential to further refine the modules within MCSC processes and automate tasks.This paper, therefore, aims to develop a new workflow engine that combines blockchain-enabled smart contracts, RPA, and related visualization technologies to address the coordination challenges inherent in MCSC.Demanddriven process modeling and smart contracts conversion with RPA actions are conducted with the MCSC coordination unit configuration, and the initial system is developed and validated in a realworld case study.Industrial requirements and feedback are collected and analyzed via questionnaires and interviews.Finally, practical implications are discussed, and the integration of RPA and AI is identified as a promising exploration for future work in MCSC coordination.
In today's world, the need for smart buildings along with smart interior design is quickly growing, requiring advanced AI-based methods for better area usage, power conservation as well as safety. Usual methods battle in continuing real-time adaptability, with several security concerns, and in sufficient data processing, making them inadequate for multidimensional architectural and interior design systems. For countering these challenges, this research introduces DesignTwin-SDN, a Digital Twin-based AI system in combination with CRL-Net, a Deep Learning (DL)-based clever model fusing CNN, ResNet-50, and LSTM for the creation of more precise spatial-temporal analysis and anomaly detection. Also, for possessing strong security, the system includes Adaptive Flow-Encrypted AES (AFEA), a dual-mode encryption strategy of combining Advanced Encryption Standard (AES) with Flow-Based Dynamic Encryption (FBDE). Furthermore, Starfish-Orangutan Optimization Algorithm (SOOA), which is a combination of the Starfish Optimization Algorithm (SFO) with Orangutan Optimization Algorithm (OOA), is proposed for the selection of the optimal secret key for purposes of maximizing that encryption efficiency. The Zero-Knowledge Proof (ZKP) system further secures authentication by precluding forbidden use in smart spaces. Experimental results show the suggested framework's effectiveness. These results show a 99.05% accuracy and a 98.51% recall, a large increase over the current method. DesignTwin-SDN merges DL and digital twins with SDN-IoT to change smart architecture and interior layout planning into more secure, efficient, and flexible systems with dynamic environments.
Qazi Muhammad Osama, Usman Ali, Tahira Ali, Danish Ali
The rapid rate of technological development necessitates a comprehensive and morally sound framework to guarantee acceptable integration between commercial innovation, mechanical systems, and artificial intelligence (AI). This review article presents a unified approach to integrated technology management by examining the intersection of future business models, mechanical sustainability, and AI ethics. The study emphasizes the significance of matching innovation with long-term environmental and societal objectives by analyzing the ethical ramifications of AI deploymentâsuch as algorithmic bias, transparency, and accountabilityâas well as developments in sustainable mechanical engineering, such as eco-efficient machinery, lifecycle optimization, and circular manufacturing. Additionally, it explores revolutionary business models that are changing value generation and operational efficiency in the contemporary technology ecosystem, including platform economies, digital twins, decentralized finance (DeFi), and Industry 5.0 frameworks. Cross-sectoral synergies that support scalability, equality, and resilience are given particular attention. In order to balance the ethical use of AI with sustainable engineering methods and progressive entrepreneurship, the assessment also emphasizes the crucial roles that legislative frameworks, data governance, and stakeholder collaboration play. In the end, this integrated viewpoint offers practical advice to academics, politicians, and business executives working to create technology systems that are nimble, sustainable, and responsible in a time of complexity and ongoing innovation.
Silvio Meneguzzo, Nicolò Bertozzi, Marco Sacchet, Lucio Rocco Inglese ¡ 5 authors
This paper introduces the EU-DREAM initiative, which combines Blockchain/Distributed Ledger Technology (DLT) and Digital Twin (DT) to achieve secure, transparent, and consumer-centric energy services. We discuss the high-level system architecture, emphasising how DLT ensures data integrity and how DT enable real-time scenario and historical analysis with DLT integrity-certified data for users. We describe the core platform layers, detail the blockchainâdigital twin integration, and present application scenarios focusing on community-scale energy trading, demand flexibility, and microgrids. We conclude with a discussion of future development steps and the challenges of ensuring privacy, scalability, and compliance with EU data regulations.
Giovanni De Gasperis, Sante Dino Facchini, Asif Saeed
In recent years, numerous regions worldwide have experienced devastating natural disasters, leading to significant structural damage to buildings and loss of human lives. The reconstruction process highlights the need for a reliable method to document and track the maintenance history of buildings. This paper introduces a novel approach for managing and monitoring restoring interventions using a secure and transparent digital framework. We will also present an application aimed at improving building structures with respect to earthquake resistance. The proposed system, referred as the âBuilding Ledger Dossierâ, leverages a Digital Twin approach applied to blockchain to establish an immutable record of all structural interventions. The framework models buildings using OpenSees, while all maintenance, repair activities, and documents are registered as Non-Fungible Tokens on a blockchain network, ensuring timestamping, transparency, and accountability. A Decentralized Autonomous Organization oversees identity management and work validation, enhancing security and efficiency in building restoration efforts. This approach provides a scalable and globally applicable solution for improving both ante-disaster monitoring and post-disaster reconstruction, ensuring a comprehensive, verifiable history of structural interventions and fostering trust among stakeholders. The proposed method is also applicable to other types of processes that require the aforementioned properties for document monitoring, such as the life-cycle management of tax credits and operations in the financial or banking sectors.
The article investigates the problem of ensuring the veracity and traceability of production data in digital factories, where EU regulatory requirements and a high level of counterfeiting create a critical deficit of trust in source information. The objective of this study is to analyze the architectures of blockchain solutions for data verification in supply chains and to develop a phased implementation plan that considers regulatory obligations and the protection of trade secrets. The novelty lies in a combined approach: classification of DLT networks according to scalability, cost, and privacy criteria; use of Merkle trees and zero-knowledge proofs to preserve confidential data while proving authenticity; and justification of architecture choice through practical case studies (IBM Food Trust, VeChain, Airbus/Circularise, SAP). The study demonstrates that blockchain enables a reduction in batch traceability time from days to seconds, a reduction in manual operations to 67%, and an increase in data matching accuracy to 92%. However, the immutability of the ledger does not eliminate the immutable garbage problem: the veracity of records depends on sensor calibration and procedural control, which requires preliminary semantic normalization and master data management. A phased implementation enables the minimization of risks and the assessment of economic impacts. To comply with DPP, it is recommended to introduce decentralized identifiers (DID) and Verifiable Credentials, as well as the integration of zero-knowledge proofs. Thus, blockchain transitions from a trial technology to a necessary component of the practical infrastructure for sustainable production chains. This article will help managers and experts in digitalization and supply chain management.