Blockchain-enabled Smart Research Articles

Blockchain-Enabled Smart Contracts Revolutionizing Supply Chain Management: A Case Study

Inefficiencies, a lack of transparency, and trust issues are common challenges in today's globalized and complex supply chains. Smart contracts combined with the decentralized, immutable ledger system of blockchain technology have made it appear like a viable answer to these problems. The application of blockchain-enabled smart contracts to supply chain management is examined in this research paper's case study. This study explores the potential of blockchain technology to improve supply chain efficiency, traceability, and transparency by closely examining a real-world case. This case study explores the planning, execution, and results of incorporating smart contracts and blockchain technology into different phases of the supply chain, such as manufacturing, distribution, logistics, and procurement. The study also addresses the advantages, difficulties, and lessons discovered during the implementation of blockchain-enabled smart contracts, offering insightful information to enterprises thinking about implementing such systems. The results demonstrate how blockchain technology has the ability to completely transform supply chain management by increasing stakeholder collaboration, lowering costs, minimizing risks, and fostering trust. This case study adds to the expanding body of research on supply chain management applications of blockchain technology and provides useful advice for companies looking to use blockchain technology to improve their operations and gain a competitive edge in the fast-paced market of today

BIM- and blockchain-enabled Automatic Procurement System (BBAPS) removing relationship bias

In the subcontractor (Sub) procurement process, the General Contractor (GC) can seek potential Subs from a limited pool based on their past relationships. This challenges new subcontractors who are qualified for the project but lack prior relationships with the GC. Furthermore, it creates a relationship bias that impedes the creation of a constructive business environment where potential Subs are encouraged to enhance their quality and compete fairly to secure procurement contracts. To address these challenges, this paper proposes a proof-of-concept of a transformational procurement system that integrates blockchain-enabled smart contracts and Building Information Modeling (BIM)-based project management. The proposed system can facilitate the data-driven automatic matching of GC with Subs, thus extending the pool of Subs and eliminating relationship bias in the procurement proceedings to enhance the effectiveness and fairness of the procurement. It contributes to the body of knowledge by enabling a digitalized and automated subcontractor procurement leveraging blockchain.

Securing blockchain-enabled smart health care image encryption framework using Tinkerbell Map

IoT enables the emergence and implementation of smart devices to address real-world problems and challenges. Today we are surrounded by various smart devices, such as smart phones, smart homes, smart cars, smart televisions, and smartwatches that assist us in making our lives easier and smoother. IoT is a conglomeration of multiple technologies at various layers to impart the best of ubiquitous and pervasive computing to deliver several benefits in a variety of application sectors such as medicine, agriculture, and industry. In an IoT setting, blockchain technology is used for addressing security challenges and eradicating third-party participation. Utilizing public networks for storing or transmitting health care images poses risks of eavesdropping, data breaches, and unauthorized access. Before uploading medical data to the decentralized network, encryption is required to prevent unauthorized access. The aim of this study is to integrate technologies to ensure transactions are conducted safely and securely. We proposed an IoT-Blockchain system based on chaos encryption scheme using Tinkerbell mapping to ensure medical data integrity and authenticity. The suggested approach is examined to assess performance parameters such as, key space analysis, key sensitivity analysis, Information Entropy (IE), histogram, correlation of adjacent pixels, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Structural Similarity Index (SSIM). These findings demonstrated that the suggested method is extremely efficient in avoiding security breaches and guaranteeing information integrity.

A roadmap for overcoming barriers to implementation of blockchain-enabled smart contracts in sustainable construction projects

A roadmap for overcoming barriers to implementation of blockchain-enabled smart contracts in sustainable construction projects

Enhancing fraud detection efficiency in mobile transactions through the integration of bidirectional 3d Quasi-Recurrent Neural network and blockchain technologies

Cases of financial fraud are increasing despite recent technical breakthroughs. It is tough to find authentic financial transaction data due to privacy issues and a lack of inter-organization synergy. However, for technologies based on data, such as machine learning to function accurately inside practical systems, they require actual data. This manuscript proposes a Fraud Detection (FD) Efficiency in Mobile Transactions through the Integration of Bidirectional 3D Quasi-Recurrent Neural Networks and Proof of Voting consensus Blockchain Technologies (Bi-3DQRNN-PoV-FD-MT). A dataset of Bitcoin transactions is employed in the suggested model. The banking sector’s Bitcoin transactions serve as the foundation for this dataset. Then the data balancing is performed using a Self-Adaptive Synthetic Over-Sampling Technique (SASOS). Then, the proposed framework utilizes the Bi-3DQRNN to determine if the information is fraudulent or not. Moreover, an intelligent Enhanced Artificial Gorilla Troops (EAGTO) Optimization algorithm is introduced to tune the weights of the model parameters. A blockchain-based proof of Voting (PoV) consensus algorithm is integrated with the proposed model for forecasting upcoming transactions. The developed scheme is instigated in Python and the performance provides 12.09%, 8.91%, and 6.92% higher accuracy compared with existing techniques like K-nearest neighbor- Distributed Blockchain Consortium (KNN-DBC), Decision tree-Ethereum blockchain-enabled smart contract (DT-EBSC) and Heterogeneous Graph Transformer Networks-Ethereum smart contract (HGTN-ESC).

Blockchain-enabled smart contracts for supply chain transformation

Blockchain-enabled smart contracts for supply chain transformation

Integration of Blockchain-Enabled Smart Contracts in Construction: SWOT Framework and Social Network Analysis

The construction sector, one of the most ancient industries globally, holds a crucial role in the progress and development of societies. However, it faces persistent productivity and efficiency challenges, rendering it a relative setback when compared to other sectors. In the ever-evolving landscape of the construction industry, characterized by complex projects, numerous stakeholders, and intricate contractual agreements, the integration of emerging technologies presents an unprecedented opportunity for transformation. Smart contracts (SCs), underpinned by blockchain (BC) technology, hold the potential to streamline and revolutionize traditional construction processes. Current literature shows a lack of comprehensive quantitative understanding of how Blockchain-enabled Smart Contracts (BSC) can affect the construction sector. To address this gap, the authors have (1) conducted a systematic keyword analysis of literature on SC in construction from Scopus and Web of Science (WoS) databases; (2) conducted a strengths–weaknesses–opportunities–threats (SWOT) analysis of BSC’s adoption in the construction industry from 174 peer-reviewed papers; (3) identified a holistic list of 72 factors steering BSC adoption in construction, categorized into the 4 aspects of the SWOT framework; (4) performed social network analysis (SNA) to quantitively assess the literature in terms of the identified factors; and (5) conducted clustering analysis to categorize combination of factors frequently highlighted in research publications into common groups. This research offers a comprehensive and methodical evaluation of the potential advantages, applications, and challenges associated with integrating BSC in the construction industry. The findings of SNA and clustering reveal a notable lack of investigation into certain combinations of factors in existing academic research. This disparity and the ensuing knowledge gaps may affect SC’s adoption in the construction sector. To this end, this study equips stakeholders with the insights necessary to make informed decisions in this rapidly evolving sector and contributes to a roadmap for future BSC construction-related research. Doi: 10.28991/CEJ-2024-010-05-020 Full Text: PDF

Blockchain-enabled Smart Contracts and the Internet of Things: Advancing the research agenda through a narrative review

Blockchain-enabled Smart Contracts and the Internet of Things: Advancing the research agenda through a narrative review

Research on Blockchain-Enabled Smart Grid for Anti-Theft Electricity Securing Peer-to-Peer Transactions in Modern Grids.

Electricity theft presents a significant financial burden to utility companies globally, amounting to trillions of dollars annually. This pressing issue underscores the need for transformative measures within the electrical grid. Accordingly, our study explores the integration of block chain technology into smart grids to combat electricity theft, improve grid efficiency, and facilitate renewable energy integration. Block chain's core principles of decentralization, transparency, and immutability align seamlessly with the objectives of modernizing power systems and securing transactions within the electricity grid. However, as smart grids advance, they also become more vulnerable to attacks, particularly from smart meters, compared to traditional mechanical meters. Our research aims to introduce an advanced approach to identifying energy theft while prioritizing user privacy, a critical aspect often neglected in existing methodologies that mandate the disclosure of sensitive user data. To achieve this goal, we introduce three distributed algorithms: lower-upper decomposition (LUD), lower-upper decomposition with partial pivoting (LUDP), and optimized LUD composition (OLUD), tailored specifically for peer-to-peer (P2P) computing in smart grids. These algorithms are meticulously crafted to solve linear systems of equations and calculate users' "honesty coefficients," providing a robust mechanism for detecting fraudulent activities. Through extensive simulations, we showcase the efficiency and accuracy of our algorithms in identifying deceitful users while safeguarding data confidentiality. This innovative approach not only bolsters the security of smart grids against energy theft, but also addresses privacy and security concerns inherent in conventional energy-theft detection methods.

AI-assisted Blockchain-enabled Smart and Secure E-prescription Management Framework

Traditional medical prescriptions based on physical paper-based documents are prone to manipulation, errors, and unauthorized reproduction due to their format. Addressing the limitations of the traditional prescription system, e-prescription systems have been introduced in several countries. However, e-prescription systems lead to several concerns like the risk of privacy loss, the problem of double-spending prescriptions, lack of interoperability, and single point of failure, all of which need to be addressed immediately. We propose an AI-assisted blockchain-enabled smart and secure e-prescription management framework to address these issues. Our proposed system overcomes the problems of the centralized e-prescription systems and enables efficient consent management to access prescriptions by incorporating blockchain-based smart contracts. Our work incorporates the Umbral proxy re-encryption scheme in the proposed system, avoiding the need for repeated encryption and decryption of the prescriptions when transferred between different entities in the network. In our work, we employ two different machine learning models(Random Forest classifier and LightGBM classifier) to assist the doctor in prescribing medicines. One is a drug recommendation model, which is aimed at providing drug recommendations considering the medical history of the patients and the general prescription pattern for the particular ailment of the patient. We have fine-tuned the SciBERT model for adverse drug reaction detection. The extensive experimentation and results show that the proposed e-prescription framework is secure, scalable, and interoperable. Further, the proposed machine learning models produce results higher than 95%.

Secure and Sustainable Energy Distribution through Blockchain Technology in Smart Grids

The incorporation of blockchain technology into smart grids is seen as a revolutionary method to bolster security and sustainability in energy distribution. This study offers a thorough examination of how blockchain, acting as a decentralized ledger, can be used within smart grids to facilitate secure energy transactions, manage distributed energy resources, and support peer-to-peer energy trading. The research investigates how blockchain's architectural deployment can mitigate cyber security risks, lower operational costs, and enhance transparency in energy transactions. It also explores how blockchain's ability to maintain immutable records aligns with smart grid technologies, suggesting a new framework that utilizes smart contracts to automate energy distribution protocols. Simulation findings indicate that integrating blockchain significantly boosts energy distribution efficiency while safeguarding data privacy and integrity. Additionally, the paper discusses the environmental benefits, illustrating how blockchain can optimize renewable energy sources within smart grids, ultimately reducing carbon emissions. The proposed model addresses the scalability challenge in blockchain networks, ensuring that the advantages of this integration are achieved without sacrificing smart grid operations' performance. This research sets the stage for future investigations into the resilience and adaptability of blockchain-enabled smart grids in meeting evolving energy needs.

Reputation Value-Based Converged Dual-Channel Digital Forensics for Blockchain-Enabled Smart Vehicles

Reputation Value-Based Converged Dual-Channel Digital Forensics for Blockchain-Enabled Smart Vehicles

Criteria for Implementing Smart Contract Technology for Hr Practitioners

ABSTRACT: It is widely held that smart contracts on a blockchain possess several unique properties, including immutability, disintermediation, and enhanced security, that can be advantageous to organizations. In particular, having these properties can enable smart contracts to benefit human resources departments in a number of ways, including applicant verification, tracking employee skills and tasks, and facilitating compensation. However, it is also reported that effectively implementing smart contracts involves a number of challenges to HR managers. To address these challenges, it would be valuable to establish criteria to help HR managers employ smart contracts successfully. The purpose of this paper is to develop a set of such criteria. The paper first provides an overview of the nature of blockchain and smart contracts and then, based on a review of relevant literature, describes how implementation of blockchain-enabled smart contracts in an HR department may benefit an organization by producing transaction cost savings through expediting processes, enhancing security, and reducing intermediaries. The paper then focuses on various challenges that have been identified in the literature to the successful use of smart contracts. These include issues regarding smart contract integrity, immutability, and security, as well as potential problems associated with a variety of legal issues. Synthesizing this information, the paper develops a set of best practice guidelines to help HR managers determine whether and how to employ smart contracts successfully for HR-related processes. The guidelines emphasize the importance of initial understanding and testing of planned smart contracts, protecting security by ensuring that only permissioned people can access smart contract data, and guaranteeing the integrity of smart contracts by paying very close attention to the translation of natural to programming language and establishing robust reviews of programmed contracts. Policy implications of the guidelines include the importance of HR departments ensuring that all employees who are involved in implementing the technology have a good understanding of the nature and capabilities of smart contracts, that robust methods be implemented to guarantee that the contracts are correctly programmed, and that HR managers keep abreast of legislative environment related to legal issues that may affect their department’s use of smart contracts.

Blockchain i upravljanje ljudskim resursima

Previous research has shown that implementing blockchain technology in businesses can lead to more secure and efficient processes in various organizational areas, including human resource management. This review paper examines the use of blockchain in human resources departments from the perspective of transaction cost economics theory, which identifies several fundamental variables that increase transaction costs for firms. These variables include bounded rationality, the pervasive possibility of opportunistic behavior, and uncertainty. The paper explores how blockchain implementation, including blockchain-enabled smart contracts, can mitigate these challenges. The paper also identifies some limitations to using blockchain and smart contracts that may increase transaction costs and thus reduce transaction cost savings.

Blockchain-enabled smart agriculture: Enhancing data-driven decision making and ensuring food security

Agriculture plays a vital role in global food security, but conventional practices have led to environmental degradation and health risks due to excessive use of agricultural nutrients and chemicals. In this era of increased consumer awareness and preference for organic food, the challenge lies in making informed choices amidst various crop production options. To address this, the present research introduces a groundbreaking study that utilizes blockchain technology to record and trace information on crop production from seeds to end-user consumption, enabling easy consumer choices. This study introduces a model that integrates Internet of Things (IoT) sensors to monitor the impact of selected chemicals and nutrients used in agriculture to enhance production yields. To ensure sustainability, the study employs the low-energy adaptive clustering hierarchy (LEACH) protocol, which optimizes energy consumption and network stability, thereby avoiding disruptions. Results indicate that different fertilizers affect soil physical properties such as temperature and moisture. These parameters are monitored using the Agriculture Vercel App, equipped with temperature, moisture, and light sensors in agricultural fields. The app provided threshold readings via alert notifications, revealing significant fluctuations in temperature (12%–43%) and moisture (83%–41%) concentrations upon the application of specific fertilizers like “Agricultural lime” and “Calcium Ammonium Nitrate.” Our IoT-based model is linked with private blockchain technology to prioritize consumer choice and facilitate transparency. This integration enhances food security while mitigating environmental degradation risks. By providing a comprehensive record of crop production practices, our model empowers consumers to make informed decisions aligned with their health and environmental concerns. This research demonstrates the potential of combining IoT and blockchain technologies to revolutionize agriculture, ensure sustainable practices, and promote food security. The findings offer significant implications for policymakers, farmers, and consumers, fostering a more sustainable and health-conscious approach to agriculture worldwide.

Blockchain-Enhanced Smart Contract for Cost-Effective Insurance Claims Processing

Blockchain-enabled smart contracts have revolutionized the insurance industry due to their potential to streamline backend operations, mitigate fraudulent claims, and enhance data security and transparency. Guided by the design science methodology, the authors propose two specific smart contract frameworks to enhance insurance claims processing related to vehicle damage claims and personal injury claims. These proposed frameworks can improve the overall efficiency and effectiveness of insurance claims processing by automating claims submission, review, analysis, and payment, while reducing fraud and data leakage, by merging various data sources and disintermediation. Furthermore, the authors design a smart contract template supported by eight operational algorithms to facilitate the processing of insurance claims with the help of smart contracts. This template provides practitioners with a standardized prototype for the development of secure and efficient insurance applications.

A knowledge framework for blockchain-enabled smart contract adoption in the construction industry

PurposeA novel facet of the construction industry's (CI) digital transformation relates to the rise of smart contracts, and the contribution of blockchain technology in this domain appears to be nascent but rapidly gaining traction. Although the benefits of digitalisation for technologically less enthusiastic CI are irrefutable, the adoption of smart contracts has been found to be low pertaining to industry professionals' behavioural factors stimulated by technological perception. The challenge undertook by this study, therefore, is to develop a knowledge framework for blockchain-enabled smart contract adoption in the CI.Design/methodology/approachFrom a methodological perspective, this study employed a qualitative approach that involved semi-structured interviews with ten (10) highly experienced CI practitioners involved in digital innovations for data collection. Directed content analysis was performed using NVivo 12 software, which enabled the creation of preliminary open codes. Subsequently, these open codes were grouped into similar categories to develop axial codes. Finally, the study presented final themes along with their corresponding descriptions.FindingsNotably, research findings expanded the current body of knowledge on perceived attributes and their measurement items to determine the perception of innovation adoption in CI, where a total of nine (9) perceived attributes were associated with thirty-two (32) measurement items.Originality/valueThe measurement items were seen as having an extensive impact on the CI professionals' decision to adopt blockchain-enabled smart contracts. With ensuing implications, this study represents one of the first to present a knowledge framework exclusively customised for blockchain-enabled smart contracts, laying the groundwork for effective technological adoption by CI professionals.

Detection and Analysis of Ethereum Energy Smart Contracts

As blockchain technology advances, so has the deployment of smart contracts on blockchain platforms, making it exceedingly challenging for users to explicitly identify application services. Unlike traditional contracts, smart contracts are not written in a natural language, making it difficult to determine their provenance. Automatic classification of smart contracts offers blockchain users keyword-based contract queries and a streamlined effective management of smart contracts. In addition, the advancement in smart contracts is accompanied by security challenges, which are generally caused by domain-specific security breaches in smart contract implementation. The development of secure and reliable smart contracts can be extremely challenging due to domain-specific vulnerabilities and constraints associated with various business logics. Accordingly, contract classification based on the application domain and the transaction context offers greater insight into the syntactic and semantic properties of that class. However, despite initial attempts at classifying Ethereum smart contracts, there has been no research on the identification of smart contracts deployed in transactive energy systems for energy exchange purposes. In this article, in response to the widely recognized prospects of blockchain-enabled smart contracts towards an economical and transparent energy sector, we propose a methodology for the detection and analysis of energy smart contracts. First, smart contracts are parsed by transforming code elements into vectors that encapsulate the semantic and syntactic characteristics of each term. This generates a corpus of annotated text as a balanced, representative collection of terms in energy contracts. The use of a domain corpus builder as an embedding layer to annotate energy smart contracts in conjunction with machine learning models results in a classification accuracy of 98.34%. Subsequently, a source code analysis scheme is applied to identified energy contracts to uncover patterns in code segment distribution, predominant adoption of certain functions, and recurring contracts across the Ethereum network.

A Smart-Contract-Aided Plastic Credit Scheme

Researchers estimate that more than 8.3 billion tonnes of plastic have been produced since the early 1950s; however, only 9% of all plastic waste ever produced has been recycled. In this article, we propose a plastic credit driven system consisting of a recyclability index (RI) and plastic credit to impel plastic recycling and increase the quality of recyclable plastics through a market self-regulation mechanism. The RI is designed to evaluate the recyclability value of different plastic products based on their material compositions. The plastic credit, defined by the quantitative relation between the RI and product information, can be issued or traded by system stakeholders. Instead of setting rigid industry standards to regulate plastic quality, we construct a governance community among industry participants using blockchain-enabled smart contracts to self-regulate and monitor plastic production and trading. The proposed system is constructed on a consortium blockchain and a public blockchain to negotiate the RI, issue credits, and trade credits using smart contracts. Through the overall system performance analysis, the experimental results demonstrate that the designed plastic credit system can promote a demand shift toward plastic products with higher plastic recyclability and achieve a lightweight operation for resource requirements and system maintenance.

Critical Factors Influencing Adoption of Blockchain-Enabled Smart Contracts in Construction Projects

Construction projects are premised upon contractual arrangements, and contracts constitute the basis of their success. A contract enables execution of work and transfer of payments, tracking of key performance indicators, and facilitation of collaboration among project stakeholders. Historically, construction projects have faced critical challenges due to poor alignment between clients’ expectations, contract terms, and contractor performance. The advent of advanced digital technologies under the concept of Industry 4.0 has the potential to benefit construction projects through application of blockchain-enabled smart contracts. However, the adoption of smart contracts in construction projects is in its early stages, and the factors that will influence its adoption remain unclear. Therefore, this study aimed to explore and establish the critical factors influencing adoption of smart contracts in construction contractual arrangements. This study administered an international questionnaire survey among experienced construction practitioners with involvement in smart contract initiatives and activities. The results obtained from descriptive statistics and fuzzy set-based analysis show that trialability, relative advantage, competitive advantage, and compatibility of smart contracts are the important predictors of the adoption of such contracts. The findings suggest that practitioners share a view that technological characteristics of blockchain-enabled smart contracts are critical to their adoption, regarding the technology’s perceived practicality in improving effectiveness and efficiency of construction projects. This study contributes to technology diffusion research in construction and highlights drivers that require practitioners’ and industry leaders’ attention to ensure successful adoption of smart contracts for cost-effective delivery of construction projects.