Steve Huckle, Rituparna Bhattacharya, Martin White
et al.
This paper explores how the Internet of Things and blockchain technology can benefit shared economy applications. The focus of this research is understanding how blockchain can be exploited to create decentralised, shared economy applications that allow people to monetise, securely, their things to create more wealth. Shared economy applications such as Airbnb and Uber are well-known applications, but there are many other opportunities to share in the digital economy. With the recent interest in the Internet of Things and blockchain, the opportunity exists to create a myriad of sharing applications, e.g. peer-to-peer automatic payment mechanisms, foreign exchange platforms, digital rights management and cultural heritage to name but a few. While many types of shared economy scenarios are proliferating, few of them, so far, leverage the Internet of Things and blockchain as technologies to build distributed applications. This paper discusses how we might make use of the Internet of Things and blockchains to create secure shared economy distributed applications. Presented are examples of such distributed applications in the context of an Internet of Things architecture using blockchain technology.
Blockchain has become a new frontier of venture capitals that has attracted the attention of banks, governments, and other business corporations. The recent blockchain related attempts included legal blockchains by Fadada.com and Microsoft and pork tracking blockchains by Walmart and IBM. Blockchain is poised to become the most exciting invention after the Internet; while the latter connects the world to enable new business models based on online business processes, the former will help resolve the trust issue more efficiently via network computing. In this paper, we give an overview on blockchain research and development as well as introduce the papers in this special issue. We show that while blockchain has enabled Bitcoin, the most successful digital currency, its widespread adoption in finance and other business sectors will lead to many business innovations as well as many research opportunities.
In response to the problems of single point of failure risk and poor scalability in current network security construction, this article applies an information model operation and maintenance data network security construction method based on partitioned blockchain. The effectiveness and advantages of the partitioned blockchain method used is evaluated in a comparison with traditional models. The research results show that the overall recall rate of the adopted method for daily network attacks is very high. Compared with traditional models, the CPU and memory usage are lower, ensuring the scalability and efficiency of blockchain while achieving a more reliable information operation and maintenance.
The globalization of agri-food supply chains has heightened consumer demand for transparency, accountability, and food safety, particularly in high-value sectors such as beef. Traditional centralized traceability systems face persistent challenges, including fragmented data, fraud risks, and delayed recall responses. Blockchain technology (BCT) emerges as a transformative solution, offering a decentralized, immutable, and transparent permissioned ledger capable of addressing these systemic weaknesses. This review comprehensively examines the application of BCT in the beef supply chain. Key findings indicate that blockchain’s core attributes—decentralization, immutability, and a shared, auditable ledger—enable robust farm-to-fork tracking, deter food fraud, and accelerate targeted product recalls. Separately, when integrated with the Internet of Things (IoT) for automated, tamper-resistant data capture and with Artificial Intelligence (AI) for predictive analytics, deployments can further improve cold-chain assurance and enable early warning of spoilage or non-compliance. However, widespread adoption faces considerable hurdles, including technical challenges related to scalability and interoperability, economic considerations regarding implementation costs, organizational resistance to change, and the need for clear regulatory frameworks and industry-wide data standards. These constraints are often more acute in low- and middle-income countries, where smallholders face higher relative onboarding costs, gaps in digital infrastructure and standards, and limited institutional capacity for implementation. Drawing on established pilots—such as Walmart’s IBM Food Trust deployment that reduced trace-back time from nearly seven days to 2.2 seconds, JD.com and Kerchin’s QR-code-enabled beef traceability system for Chinese consumers, and JBS’s blockchain-based Transparent Livestock Farming Platform for supplier monitoring—this review highlights blockchain’s practical feasibility in real-world beef supply chains. Ultimately, blockchain offers a profound opportunity to enhance beef safety, quality, and trust, while also underscoring the need for concerted research efforts and multi-stakeholder collaboration to overcome barriers and fully realize its capabilities.
Machine-to-machine (M2M) communication within the Internet of Things (IoT) faces increasing security and efficiency challenges as networks proliferate. Existing approaches often struggle with balancing robust security measures and energy efficiency, leading to vulnerabilities and reduced performance in resource-constrained environments. To address these limitations, we propose SAFE-CAST, a novel secure AI-federated enumeration for clustering-based automated surveillance and trust framework. This study addresses critical security and efficiency challenges in M2M communication within the context of IoT. SAFE-CAST integrates several innovative components: (1) a federated learning approach using Lloyd’s K-means algorithm for secure clustering, (2) a quality diversity optimization algorithm (QDOA) for secure channel selection, (3) a dynamic trust management system utilizing blockchain technology, and (4) an adaptive multi-agent reinforcement learning for context-aware transmission scheme (AMARLCAT) to minimize latency and improve scalability. Theoretical analysis and extensive simulations using network simulator (NS)-3.26 demonstrate the superiority of SAFE-CAST over existing methods. The results show significant improvements in energy efficiency (21.6% reduction), throughput (14.5% increase), security strength (15.3% enhancement), latency (33.9% decrease), and packet loss rate (12.9% reduction) compared to state-of-the-art approaches. This comprehensive solution addresses the pressing need for robust, efficient, and secure M2M communication in the evolving landscape of IoT and edge computing.
Tilly Raycitra Widya, Dede Cahyadi, Duta Arief Christanto
et al.
This study develops a comprehensive Hybrid AI-Cloud conceptual model to enhance government information systems through digital transformation. Using a systematic literature review (PRISMA protocol) of 51 publications (2020-2025) from Scopus, IEEE Xplore, and ScienceDirect, we identify four critical components: a hybrid architecture combining private and public clouds achieves 97.46% prediction accuracy but faces interoperability challenges in Indonesia where 85% of agencies use disparate systems; layered security with Hyperledger Fabric blockchain reduces data breaches by 72%, though 65% of Indonesian institutions lack CSIRT teams; user-centric designs score 76.88 on SUS scales yet encounter 71% civil servant resistance to AI automation; and organizational adoption strategies based on UTAUT frameworks are hindered by only 12% of civil servants having digital certifications. The research reveals Indonesia's significant gaps in system integration, cybersecurity preparedness, and digital literacy compared to global leaders like Estonia and Singapore. Successful implementation requires standardized cloud architectures with API gateways, mandatory cybersecurity audits, comprehensive digital training programs, and phased adoption roadmaps with change management components. While offering a holistic framework for digital government transformation, the study acknowledges limitations including literature bias toward developed nations and the need for local empirical validation through pilot projects, suggesting future research should incorporate ethical AI governance considerations alongside technical implementations.
IntroductionIt is important to enhance consumer trust in the product quality of a sustainable agricultural supply chain. However, the frequent occurrence of food safety problems in practice leads to a lack of public confidence in food safety. To tackle the challenge of quality distrust, we harness the synergistic potential of “GenAI + blockchain” technology among industry-leading agribusinesses.MethodsThree distinct models are constructed to explore the impact of various technological integrations, with a focus on analyzing inventory management, operational efficiency, and precision technology adoption using AnyLogic.ResultsOur study reveals that (1) Integrating AI and blockchain technology can modulate minimum safety stock, catalyzing leapfrog revenue growth for enterprises. (2) Harnessing artificial intelligence can bolster the agricultural supply chain’s overall efficiency, but striving to achieve the highest possible accuracy is not feasible. (3) Gauging consumers’ premium for freshness aids companies in targeting key demographics and bolstering quality trust, thus fostering a stable upward trend in sales.DiscussionBy demystifying the underpinnings of minimum safety stock adjustments and the subtle effects of precision technology, our study steers the crafting of advanced inventory strategies and astute technology decisions for innovative agribusinesses.
Nutrition. Foods and food supply, Food processing and manufacture
Jovika Nithyanantham Balamurugan, Devineni Poojitha, Ramu Jahna Bindu
et al.
Decentralized energy trading has been designed as a scalable substitute for traditional electricity markets. While blockchain technology facilitates efficient transparency and automation for peer-to-peer energy trading, the majority of current proposals lack real-time intelligence and adaptability concerning pricing strategies. This paper presents an innovative machine learning-driven solar energy trading platform on the Ethereum blockchain that uniquely integrates Bayesian-optimized XGBoost models with dynamic pricing mechanisms inherently incorporated within smart contracts. The principal innovation resides in the real-time amalgamation of meteorological data via Chainlink oracles with machine learning-enhanced price optimization, thereby establishing an adaptive system that autonomously responds to fluctuations in supply and demand. In contrast to existing static pricing methodologies, our framework introduces a multi-faceted dynamic pricing model that encompasses peak-hour adjustments, prediction confidence weighting, and weather-influenced corrections. The system dynamically establishes energy prices predicated on real-time supply–demand forecasts through the implementation of role-based access control, cryptographic hash functions, and ongoing integration of meteorological and machine learning data. Utilizing real-world meteorological data from La Trobe University’s UNISOLAR dataset, the Bayesian-optimized XGBoost model attains a remarkable prediction accuracy of 97.45% while facilitating low-latency price updates at 30 min intervals. The proposed system delivers robust transaction validation, secure offer creation, and scalable dynamic pricing through the seamless amalgamation of off-chain machine learning inference with on-chain smart contract execution, thereby providing a validated platform for trustless, real-time, and intelligent decentralized energy markets that effectively address the disparity between theoretical blockchain energy trading and practical implementation needs.
Muwafaq Jawad, Ali A. Yassin, Hamid Ali Abed Al-asadi
et al.
The Internet of Health Things (IoHT) is a network of healthcare devices, software, and systems that enable remote monitoring and healthcare services by gathering real-time health data through sensors. Despite its significant benefits for modern smart healthcare, IoHT faces growing security challenges due to the limited processing power, storage capacity, and self-defense capabilities of its devices. While blockchain-based authentication solutions have been developed to leverage tamper-resistant decentralized designs for enhanced security, they often require substantial computational resources, increased storage, and longer authentication times, hindering scalability and time efficiency in large-scale, time-critical IoHT systems. To address these challenges, we propose a novel four-phase authentication scheme comprising setup, registration, authentication, and secret construction phases. Our scheme integrates chaotic-based public key cryptosystems, a Light Encryption Device (LED) with a 3-D Lorenz chaotic map algorithm, and blockchain-based fog computing technologies to enhance both efficiency and scalability. Simulated on the Ethereum platform using Solidity and evaluated with the JMeter tool, the proposed scheme demonstrates superior performance, with a computational cost reduction of 40% compared to traditional methods like Elliptic Curve Cryptography (ECC). The average latency for registration is 1.25 ms, while the authentication phase completes in just 1.50 ms, making it highly suitable for time-critical IoHT applications. Security analysis using the Scyther tool confirms that the scheme is resistant to modern cyberattacks, including 51% attacks
and hijacking, while ensuring data integrity and confidentiality. Additionally, the scheme minimizes communication costs and supports the scalability of large-scale IoHT systems. These results highlight the proposed scheme's potential to revolutionize secure and efficient healthcare monitoring, enabling real-time, tamper-proof data management in IoHT environments. [JJCIT 2025; 11(2.000): 238-259]
Information technology, Electronic computers. Computer science
This study explores the potential of blockchain technology to optimize trade finance processes and to address inefficiencies and fraud risks in centralized systems that contribute to a growing global trade finance gap, particularly affecting SMEs. Through documentary analysis and the case of Morocco's OCP Group, with insights for practitioners, we explore the benefits and challenges of integrating blockchain into trade finance. Our findings suggest a hybrid solution integrating blockchain into existing infrastructure, relying on both off-chain and on-chain governance mechanisms in smart contracts. This approach aims to bridge the gap between traditional and blockchain solutions in trade finance and discusses the potential for a more pragmatic way forward for the industry.
This systematic review examines critical usability factors that influence the adoption of mobile health (applications among older adults) and identifies gaps in current usability models, including ISO 9241-11, Nielsen’s heuristics, and Panicoideae, Aristidoideae, Chloridoideae, Micrairoideae, Arundinoideae, Danthonioideae. This review also explores the potential role of blockchain technology in enhancing multimodal medical data systems within mHealth applications. A comprehensive search across six databases yielded 1,073 studies, with 60 meeting the inclusion criteria. Studies were analyzed through thematic synthesis to identify key success factors (RQ1) and comparative analysis to assess limitations in existing frameworks (RQ2). Key factors promoting mHealth adoption included ease of use, efficiency, error prevention, learnability, memorability, and user satisfaction. Blockchain integration emerged as a promising approach to improve data security, interoperability, and user trust, particularly for older adults who engage with complex, multimodal health data. Findings from RQ2 highlighted gaps in usability models, such as the lack of age-specific guidance for multimodal interaction, error recovery, and data privacy. These results underscore the need to define a new usability framework and incorporate blockchain to meet the unique needs of older adults in mHealth applications, supporting both secure and accessible healthcare management. This review investigates mobile health application’s integration with blockchain. This review explores user-friendly mHealth applications for older adults and also explores how blockchain can improve data systems in these applications. After analyzing 60 studies, key factors for the adoption of information technology were identified, including ease of use, efficiency, error prevention, and user satisfaction. The researchers discovered that blockchain enhances data security, interoperability, and trust of mHealth applications. Moreover, existing usability models lack elderly specific guidance, particularly for handling errors and privacy in mHealth applications. These findings highlight the need for a new usability framework tailored to older adults, integrating blockchain to ensure secure, accessible, and user-friendly healthcare management.
Computer applications to medicine. Medical informatics
Saad Hammood Mohammed, Abdulmajeed Al-Jumaily, Mandeep S. Jit Singh
et al.
The Smart Grid is a modern power grid that relies on advanced technologies to provide reliable and sustainable electricity. However, its integration with various communication technologies and IoT devices makes it vulnerable to cyber-attacks. Such attacks can lead to significant damage, economic losses, and public safety hazards. To ensure the security of the smart grid, increasingly strong security solutions are needed. This paper provides a comprehensive analysis of the vulnerabilities of the smart grid and the different approaches for detecting cyber-attacks. It examines the different vulnerabilities of the smart grid, including system vulnerabilities and cyber-attacks, and discusses the vulnerabilities of all its elements. The paper also investigates various approaches for detecting cyber-attacks, including rule-based, signature-based, anomaly detection, and ma-chine learning-based methods, with a focus on their effectiveness and related research. Finally, prospective cybersecurity approaches for the smart grid, such as AI approaches and blockchain, are discussed along with the challenges and future prospects of cyberattacks on the smart grid. The paper’s findings can help policymakers and stakeholders make informed decisions about the security of the smart grid and develop effective strategies to protect it from cyber-attacks.
In the modern era, the significance of incentive mechanisms spans a variety of fields, including the development of smart cities, the dynamics within social information networks, and the realm of online education. This study introduces an innovative incentive strategy, grounded in the use of blockchain contracts, aimed at cultivating reliable interactions among participants while simultaneously bolstering the security and effectiveness of digital learning resources. By capitalizing on the inherently decentralized architecture of blockchain technology, this research unveils a novel approach to digital learning resources, encompassing both the concept and its associated storage framework. Moreover, the study proposes a dynamic optimization model specifically designed for the blockchain of educational resources. This model is crafted to fit seamlessly within the context of real-world educational settings, taking into careful consideration the diverse viewpoints of all stakeholders engaged with particular educational materials. In the realm of practical education, particularly within the domain of computer science, this approach emphasizes the integration of pertinent learning materials into blockchain nodes, thereby addressing key educational content. By implementing a blockchain smart contract, an incentive mechanism is created that rewards both learners and resource contributors, effectively encouraging active participation in resource development and quality improvement. This mechanism effectively tackles challenges in the learning process, such as inaccurate resource access, reduced learning efficiency, and the scarcity of current, high-quality online resources. Experimental findings show that the smart contract-driven online learning resource incentive mechanism significantly improves teaching effectiveness.
Background Digital health technologies, including telemedicine, mobile health (mHealth), and remote monitoring, are playing a greater role in medical practice. Safe and accurate management of medical information leads to the advancement of digital health, which in turn results in a number of beneficial effects. Furthermore, mHealth can help lower costs by facilitating the delivery of care and connecting people to their health care providers. Mobile apps help empower patients and health care providers to proactively address medical conditions through near real-time monitoring and treatment, regardless of the location of the patient or the health care provider. Additionally, mHealth data are stored in servers, and consequently, data management that prevents all forms of manipulation is crucial for both medical practice and clinical trials. Objective The aim of this study was to develop and evaluate a tamper-resistant mHealth system using blockchain technology, which enables trusted and auditable computing using a decentralized network. Methods We developed an mHealth system for cognitive behavioral therapy for insomnia using a smartphone app. The volunteer data collected with the app were stored in JavaScript Object Notation format and sent to the blockchain network. Thereafter, we evaluated the tamper resistance of the data against the inconsistencies caused by artificial faults. Results Electronic medical records collected using smartphones were successfully sent to a private Hyperledger Fabric blockchain network. We verified the data update process under conditions where all the validating peers were running normally. The mHealth data were successfully updated under network faults. We further ensured that any electronic health record registered to the blockchain network was resistant to tampering and revision. The mHealth data update was compatible with tamper resistance in the blockchain network. Conclusions Blockchain serves as a tamperproof system for mHealth. Combining mHealth with blockchain technology may provide a novel solution that enables both accessibility and data transparency without a third party such as a contract research organization.