Search Results (72)

Blockchain is increasingly applied in the agri-food sector to enhance traceability, data integrity, and accountability. However, its broader role in food system sustainability remains insufficiently characterized, particularly when examined against global megatrends shaping future agri-food transitions. This paper investigates how blockchain technology can reinforce sustainable, inclusive, and resilient food systems under the effect of major global megatrends. A structured literature review of peer-reviewed and industry sources was conducted to identify evidence on blockchain-enabled improvements in transparency, certification, and supply chain coordination. Complementary analysis of a curated dataset of European and international pilot implementations evaluated technological architectures, governance models, and demonstrated performance outcomes. Additionally, stakeholder-based foresight activities and scenarios representing alternative blockchain adoption pathways, developed within the TRUSTyFOOD project (GA: 101060534), were used to examine the interconnection between blockchain adoption and megatrends. Evidence from the literature and pilot cases indicates that blockchain can strengthen product-level traceability and improve verification of sustainability and safety claims. Cross-case analysis also reveals persistent constraints, including heterogeneous technical standards, limited interoperability, high deployment costs for smallholders, and governance risks arising from consortium-led platforms. Blockchain can function as an enabling digital layer for sustainable and resilient food systems and should be embedded in wider, participatory strategies that align digital innovation with long-term sustainability and equity goals in the agri-food sector. Full article

The temperate Himalayan states of Jammu and Kashmir, Himachal Pradesh, Uttarakhand, Ladakh, Sikkim, and Arunachal Pradesh in India face unique agro-ecological challenges across agriculture and allied sectors, including pest and disease pressures, inefficient resource use, post-harvest losses, and fragmented supply chains. This review systematically examines 21 critical problem areas, with three key challenges identified per sector across agriculture, agricultural engineering, fisheries, forestry, horticulture, sericulture, and animal husbandry. Artificial Intelligence (AI) and Machine Learning (ML) interventions, including computer vision, predictive modeling, Internet of Things (IoT)-based monitoring, robotics, and blockchain-enabled traceability, are evaluated for their regional applicability, pilot-level outcomes, and operational limitations under temperate Himalayan conditions. The analysis highlights that AI-enabled solutions demonstrate strong potential for early pest and disease detection, improved resource-use efficiency, ecosystem monitoring, and market integration. However, large-scale adoption remains constrained by limited digital infrastructure, data scarcity, high capital costs, low digital literacy, and fragmented institutional frameworks. The novelty of this review lies in its cross-sectoral synthesis of AI/ML applications tailored to the Himalayan context, combined with a sector-wise revenue-loss assessment to quantify economic impacts and guide prioritization. Based on the identified gaps, the review proposes feasible, context-aware strategies, including lightweight edge-AI models, localized data platforms, capacity-building initiatives, and policy-aligned implementation pathways. Collectively, these recommendations aim to enhance sustainability, resilience, and livelihood security across agriculture and allied sectors in the temperate Himalayan region. Full article

The proliferation of Internet of Things (IoT) applications in safety-critical domains, such as healthcare, smart transportation, and industrial automation, demands robust solutions for data integrity, traceability, and security that surpass the capabilities of centralized databases. This paper analyzes how blockchain technology can be integrated with core IoT service functions—including data management, security, device management, group coordination, and automated billing—to enhance immutability, trust, and operational efficiency. Our analysis identifies practical use cases such as consensus-driven tamper-proof storage, role-based access control, firmware integrity verification, and automated micropayments. These use cases showcase blockchain’s potential beyond traditional data storage. Building on this, we propose a novel framework that integrates a permissioned distributed ledger with a standardized IoT service layer platform through a Blockchain Interworking Proxy Entity (BlockIPE). This proxy dynamically maps IoT service functions to smart contracts, enabling flexible data routing to conventional databases or blockchains based on the application requirements. We implement a Dockerized prototype that integrates a C-based oneM2M platform with an Ethereum-compatible permissioned ledger (implemented using Hyperledger Besu) via BlockIPE, incorporating security features such as role-based access control. For performance evaluation, we use Ganache to isolate proxy-level overhead and scalability. At the proxy level, the blockchain-integrated path achieves processing latencies (≈86 ms) comparable to, and slightly faster than, the traditional database path. Although the end-to-end latency is inherently governed by on-chain confirmation (≈0.586–1.086 s), the scalability remains high (up to 100,000 TPS). This validates that the architecture secures IoT ecosystems with manageable operational overhead. Full article

This review examines how the integration of circular bioeconomy principles with digital technologies can drive climate change mitigation, improve resource efficiency, and facilitate sustainable biorefinery development. This highlights the urgent need to transition away from fossil fuels and introduces the bio-circular economy as a regenerative model focused on biomass valorization, reuse, recycling, and biodegradability. This study compares linear, circular, and bio-circular approaches and analyzes key policy frameworks in Europe, Latin America, and Asia linked to several UN Sustainable Development Goals. A central focus is the role of digitalization, particularly artificial intelligence (AI), the Internet of Things (IoT), and blockchain. Examples include AI-based biomass yield prediction and biorefinery optimization, IoT-enabled real-time monitoring of material and energy flows, and blockchain technology for supply chain traceability and transparency. Applications in agricultural waste valorization, bioplastics, bioenergy, and nutraceutical extraction are also discussed in this review. Sustainability tools, such as automated life-cycle assessment (LCA) and Industry 4.0 integration, are outlined. Finally, future perspectives emphasize autonomous smart biorefineries, biotechnology–nanotechnology convergence, and international collaboration supported by open data platforms. Full article

This study investigates how core digital technologies—artificial intelligence (AI) and blockchain—can foster green innovation and sustainable consumption through circular platform design in high-value resale markets. Using Design Science Research (DSR) methodology, including its iterative cycles, we developed and evaluated TRUCE (Trust, Resale Logic, User Centricity, Circular Infrastructure, Ecosystem Governance), a sustainability-oriented digital architecture designed to promote ethical, energy-efficient consumption. TRUCE aims to leverage AI-driven authentication, blockchain-based transparency, and consumer data analytics, aiming to embed circularity and traceability into platform governance. Aligned with the EU Green Deal’s digital agenda, it is intended to support waste reduction, lifecycle extension, and responsible consumption, contributing to Sustainable Development Goal 12 and the broader 2030 Agenda. Full article

The rapid advancement of social media and the exponential increase in online information have made open-source intelligence an essential component of modern criminal investigations. However, existing digital forensics standards mainly focus on evidence derived from controlled devices such as computers and mobile storage, providing limited guidance for social media–based intelligence. Evidence captured from online platforms is often volatile, editable, and difficult to verify, which raises doubts about its authenticity and admissibility in court. To address these challenges, this study proposes a systematic and legally compliant open-source intelligence framework aligned with digital forensics principles. The framework comprises five stages: identification, acquisition, authentication, preservation, and validation. By integrating blockchain-based notarization and image verification mechanisms into existing forensic workflows, the proposed system ensures data integrity, traceability, and authenticity. The implemented prototype demonstrates the feasibility of conducting reliable and legally compliant open-source intelligence investigations, providing law enforcement agencies with a standardized operational guideline for social media–based evidence collection. Full article

Assisted Reproductive Technology (ART), particularly In Vitro Fertilization (IVF), generates highly sensitive medical data classified as Protected Health Information (PHI) under international privacy and data protection laws. Ensuring the secure, transparent, and ethically governed management of this data is both essential and legally mandated. However, conventional Electronic Medical Record (EMR) systems often present significant challenges, including data-integrity risks, unauthorized access, and limited patient control—issues that become especially critical in contexts such as fertility preservation for cancer patients. EmbryoTrust introduces a blockchain-based framework designed to ensure the confidentiality, integrity, and availability of IVF-related information through a private, permissioned network integrated with role-based access control (RBAC). Smart contracts, implemented in Solidity on the Ethereum platform, verify spousal identities and enforce data immutability in compliance with religious legislation and ethical regulations. Off-chain data are stored in MongoDB for scalable, privacy-preserving management, while on-chain summaries provide tamper-evident traceability and verifiable auditability. The system was deployed and validated on the Ethereum Holešky testnet using Solidity 0.8.21 and Node.js 18.17, achieving an average transaction-confirmation time of 2.8 s, 99.9% uptime and a 95% user-satisfaction rate. Functional, integration, and usability testing confirmed secure and efficient data handling with minimal computational overhead. Comparative analysis demonstrated that the hybrid on-/off-chain architecture reduces latency and gas costs while maintaining automated compliance enforcement. The modular design enables adaptation to other jurisdictions by reconfiguring ethical and regulatory parameters within the smart-contract layer, ensuring flexibility for global deployment. Overall, the EmbryoTrust framework illustrates how blockchain logic can technically enforce medical and ethical rules in real time, providing a reproducible model for secure, culturally compliant, and privacy-preserving digital-health information management. Its alignment with Saudi Vision 2030 and the Wold Health Organization (WHO) Global Strategy on Digital Health 2020–2025 highlights its potential as a scalable solution for next-generation ART information systems. Full article

(1) Background: A blockchain-based framework for distributed agile Open-Source Software for Archaeological Photogrammetry (OSSAP) testing life cycle is an innovative approach that uses blockchain technology to optimize the Open-Source Software for Archaeological Photogrammetry process. Previously, various methods have been employed to address communication and collaboration challenges in Open-Source Software for Archaeological Photogrammetry, but they were inadequate in aspects such as trust, traceability, and security. Additionally, a significant cause of project failure was the non-completion of unit testing by developers, leading to delayed testing. (2) Methods: This article discusses the integration of blockchain technology in Open-Source Software for Archaeological Photogrammetry and resolves critical concerns related to transparency, trust, coordination, testing and communication. A novel approach is proposed based on a blockchain framework named Open-Source Software for Archaeological Photogrammetry Testing-Plus. (3) Results: The Open-Source Software for Archaeological Photogrammetry Testing-Plus framework utilizes blockchain technology to provide a secure and transparent platform for acceptance testing and payment verification. Moreover, by leveraging smart contracts on a private Ethereum blockchain, Open-Source Software for Archaeological Photogrammetry Testing-Plus ensures that both the testing team and the development team are working towards a common goal and are compensated fairly for their contributions. (4) Conclusions: The experimental results conclusively show that this innovative approach substantially improves transparency, trust, coordination, testing and communication and provides security for both the testing team and the development team engaged in the distributed agile Open-Source Software for Archaeological Photogrammetry (Open-Source Software for Archaeological Photogrammetry) testing life cycle. Full article

The Blockchain-Based Medical Insurance Transaction System (BMIT) developed in this study addresses key issues in traditional medical insurance—information silos, data tampering, and privacy breaches—through innovative blockchain architectural design and technical infrastructure reconstruction. Built on a consortium blockchain architecture with FISCO BCOS (Financial Blockchain Shenzhen Consortium Blockchain Open Source Platform) as the underlying platform, the system leverages FISCO BCOS’s distributed ledger, granular access control, and efficient consensus algorithms to enable multi-stakeholder on-chain collaboration. Four node roles and data protocols are defined: hospitals (on-chain data providers) generate 3D coordinate hashes of medical data via an algorithmically enhanced Bloom Filter for on-chain certification; patients control data access via blockchain private keys and unique parameters; insurance companies verify eligibility/claims using on-chain Bloom filters; the blockchain network stores encrypted key data (public keys, Bloom filter coordinates, and timestamps) to ensure immutability and traceability. A 3D-enhanced Bloom filter—tailored for on-chain use with user-specific hash functions and key control—stores only 3D coordinates (not raw data), cutting storage costs for 100 records to 1.27 KB and reducing the error rate to near zero ($1.77\%$ lower than traditional schemes for 10,000 entries). Three core smart contracts (identity registration, medical information certification, and automated verification) enable the automation of on-chain processes. Performance tests conducted on a 4-node consortium chain indicate a transaction throughput of 736 TPS (Transactions Per Second) and a per-operation latency of 181.7 ms, which meets the requirements of large-scale commercial applications. BMIT’s three-layer design (“underlying blockchain + enhanced Bloom filter + smart contracts”) delivers a balanced, efficient blockchain medical insurance prototype, offering a reusable technical framework for industry digital transformation. Full article

Background: Type 2 diabetes (T2D) is no longer a standalone clinical condition—it has become a syndemic shaped by food insecurity, social inequality, and digital marginalization in emerging economies. This convergence calls for a reimagining of public health through intersectoral, digitally enabled, and culturally grounded approaches. This study explores how intersectoral strategies, supported by digital innovation and rooted in food sovereignty, can help prevent and manage T2D in emerging countries. Methods: A narrative review was conducted using the PubMed, Scopus, and Web of Science databases. Studies published between 2014 and 2025 were included if they addressed T2D and food security in emerging contexts, focusing on intersectoral or multisectoral strategies. Studies on T1D, non-human subjects, and high-income settings were excluded from the study. Thirty-nine studies were critically synthesized. Results: Food insecurity acts as both a biological stressor and a sociopolitical condition that worsens poor glycemic control. Promising but underutilized intersectoral strategies include agroecological food systems, school-based nutrition programs, and community health worker networks. Digital tools, such as AI-driven diagnostics, blockchain food traceability, and mobile health platforms, offer scalable solutions but face challenges in infrastructure, digital literacy, and ethical governance. Conclusions: A digitally inclusive, ethically reflexive intersectoral paradigm is needed that recognizes food and digital access as human rights. Full article

Diplomas and academic transcripts issued at the conclusion of a university cycle have been the subject of numerous studies focused on developing secure methods for their registration and access. However, in the context of high school teachers, these initial credentials mark only the starting point of a much more complex professional journey. Throughout their careers, teachers receive a wide array of certificates and attestations related to professional development, participation in educational projects, volunteering, and institutional contributions. Many of these documents are issued directly by the school administration and are often vulnerable to misplacement, unauthorized alterations, or limited portability. These challenges are amplified when teachers move between schools or are involved in teaching across multiple institutions. In response to this need, this paper proposes a blockchain-based solution built on the Ethereum platform, which ensures the integrity, traceability, and long-term accessibility of such records, preserving the professional achievements of teachers across their careers. Although most research has focused on securing highly valuable documents on blockchain, such as diplomas, certificates, and micro-credentials, this study highlights the importance of extending blockchain solutions to school-issued attestations, as they carry significant weight in teacher evaluation and the development of professional portfolios. Full article

This study investigates the structural and cyclical determinants of tropical hardwood exports among member countries of the International Tropical Timber Organization (ITTO) over the period 1995–2022—a sector historically characterized by persistent value imbalances. The central research issue addresses the enduring asymmetries in the global value chain, shaped by unequal industrial capacities, limited access to environmental certifications, and entrenched North–South trade relations. The study pursues three main objectives: (1) to develop a typology of exporting countries; (2) to estimate heterogeneous trade elasticities; (3) to propose a policy framework that reconciles equity with sustainability. The empirical findings identify four export profiles: (i) raw producers with minimal local processing; (ii) marginal players with weak trade integration; (iii) high-value-added re-export platforms (notably in Asia); (iv) major consumer markets. Trade effects vary across regions. In the short term, imports boost exports (+0.33%), particularly in re-export models seen in Asia, the USA, and the EU, while local production remains limited in Africa due to weak industrial capacity. In the long term, both domestic production and imports have a positive impact (+0.38% and +0.37%), but only countries with strong industrial bases fully benefit. Population size (+1.29%) also reinforces the advantage of large markets like China and India, supported by short-term economic growth elasticity (+1.1%), likely driven by improved logistics or rising demand from importing countries. In response, the policy implications converge around the proposal of a “Fair and Digital Timber Trade Model” (F&DTTT), structured around three pillars: (a) specialized economic zones aligned with SDGs 8, 12, and 15; (b) blockchain-based traceability systems to enhance supply chain transparency; (c) South–South cooperation strategies aimed at commercial, regulatory, and institutional rebalancing, including potential cartelization initiatives among Southern countries. Supported by a robust methodological framework, this study provides a forward-looking pathway for transforming the tropical timber trade into a vector of equity and sustainability. Full article

Digital innovation is rapidly transforming the agriculture sector, drawing attention from global development institutions, policymakers, tech firms, and scholars aimed at aligning food systems with international goals like Zero Hunger and the FAO agendas. Small and medium enterprises in agriculture (Agri-SMEs) represent a significant portion of processing and production units but face challenges in digital transformation despite their importance. Technologies such as Artificial Intelligence (AI), blockchain, cloud services, IoT, and mobile platforms offer tools to improve efficiency, access, value creation, and traceability. However, the patterns and applications of these transformations in Agri-SMEs remain fragmented and under-theorized. This paper presents a systematic review of interactions between digital transformation and innovation in Agri-SMEs based on findings from ninety-five peer-reviewed studies. Key themes identified include AI-based decision support, blockchain traceability, cloud platforms, IoT precision agriculture, and mobile technologies for financial integration. The review maps these themes against business model values and highlights barriers like capacity gaps and infrastructure deficiencies that hinder scalable adoption. It concludes with recommendations for future research, policy, and ecosystem coordination to promote the sustainable development of digitally robust Agri-SMEs. Full article

The collaborative construction of large-scale, diverse datasets is crucial for developing high-performance machine learning models. However, this collaboration faces significant challenges, including ensuring data security, protecting participant privacy, maintaining high dataset quality, and aligning economic incentives among multiple stakeholders. Effective risk management strategies are essential to systematically identify, assess, and mitigate potential risks associated with data collaboration. This study proposes a federated blockchain-based framework designed to manage multiparty dataset collaborations securely and transparently, explicitly incorporating comprehensive risk management practices. The proposed framework involves six core entities—key distribution center (KDC), researcher (RA), data owner (DO), consortium blockchain, dataset evaluation platform, and the orchestrating model itself—to ensure secure, privacy-preserving and high-quality dataset collaboration. In addition, the framework uses blockchain technology to guarantee the traceability and immutability of data transactions, integrating token-based incentives to encourage data contributors to provide high-quality datasets. To systematically mitigate dataset quality risks, we introduced an innovative categorical dataset quality assessment method leveraging label reordering to robustly evaluate datasets. We validated this quality assessment approach using both publicly available (UCI) and privately constructed datasets. Furthermore, our research implemented the proposed blockchain-based management system within a consortium blockchain infrastructure, benchmarking its performance against existing methods to demonstrate enhanced security, reliability, risk mitigation effectiveness, and incentive alignment in dataset collaboration. Full article

The blockchain technology is transforming the mining industry by enabling mineral reserve tokenization, improving security, transparency, and traceability. However, controlling access to sensitive mining data remains a challenge. Existing access control models, such as role-based access control, are too rigid because they assign permissions based on predefined roles rather than real-world conditions like mining licenses, regulatory approvals, or investment status. To address this, this paper explores an attribute-based access control model for blockchain-based mineral tokenization systems. ABAC allows access permissions to be granted dynamically based on multiple attributes rather than fixed roles, making it more adaptable to the mining industry. This paper presents a high-level system design that integrates ABAC with the blockchain using smart contracts to manage access policies and ensure compliance. The proposed model is designed for permissioned blockchain platforms, where access control decisions can be automated and securely recorded. A comparative analysis between ABAC and RBAC highlights how ABAC provides greater flexibility, security, and privacy for mining operations. By introducing ABAC in blockchain-based mineral reserve tokenization, this paper contributes to a more efficient and secure way of managing data access in the mining industry, ensuring that only authorized stakeholders can interact with tokenized mineral assets. Full article