Sri Sai Durga Mani Vasireddy, Supriya Yalagala, Jayasri Sikha, Rani Vullaganti · 7 authors
The primary objective of this project is to develop a robust and secure system that uses blockchain technology as well as Ethereum and IoT sensors to create a transparent and automated irrigation management solution for farmers. The key components of this innovative system include IoT sensors for real-time data collection, smart contracts on the Ethereum blockchain for transparent and immutable record keeping, and a user-friendly interface for farmers to monitor and control their irrigation systems remotely. The blockchain will provide data security to avoid the problem of data manipulation; because the IoT components will produce large volumes of data, the data must be securely maintained.
M. Yu. Kataev, Larisa Bulysheva, Alexander Krupskiy
Abstract The Internet of Things (IoT) constitutes a network of physical objects, including devices and systems, capable of intercommunication both among themselves and with external systems via the Internet. Its applications span across various sectors such as manufacturing, medicine, commerce, security, forestry and agriculture. The application of IoT in agriculture involves gathering data from diverse sensors, offering timely and precise solutions. This technology facilitates the reduction of manual labour involved in tasks like animal monitoring, greenhouse management and field surveillance. Integrated sensors within the IoT framework enable the collection of data pertaining to soil, air, water, animal tracking, plant growth and other relevant metrics. Nevertheless, the swift evolution of IoT presents a susceptibility to unauthorized access and compromises in data security. To address this concern, the utilization of blockchain technology has been recommended. This paper proposes a novel IoT architecture integrated with blockchain technology to enhance data security in agricultural applications. A detailed schematic has been devised and implemented in software to illustrate this approach.
Inas Al Khatib, Abdulrahim Shamayleh, Malick Ndiaye
In recent years, the Internet of medical things (IoMT) has become a significant technological advancement in the healthcare sector. This systematic review aims to identify and summarize the various applications, key challenges, and proposed technical solutions within this domain, based on a comprehensive analysis of the existing literature. This review highlights diverse applications of the IoMT, including mobile health (mHealth) applications, remote biomarker detection, hybrid RFID-IoT solutions for scrub distribution in operating rooms, IoT-based disease prediction using machine learning, and the efficient sharing of personal health records through searchable symmetric encryption, blockchain, and IPFS. Other notable applications include remote healthcare management systems, non-invasive real-time blood glucose measurement devices, distributed ledger technology (DLT) platforms, ultra-wideband (UWB) radar systems, IoT-based pulse oximeters, accident and emergency informatics (A&EI), and integrated wearable smart patches. The key challenges identified include privacy protection, sustainable power sources, sensor intelligence, human adaptation to sensors, data speed, device reliability, and storage efficiency. The proposed mitigations encompass network control, cryptography, edge-fog computing, and blockchain, alongside rigorous risk planning. The review also identifies trends and advancements in the IoMT architecture, remote monitoring innovations, the integration of machine learning and AI, and enhanced security measures. This review makes several novel contributions compared to the existing literature, including (1) a comprehensive categorization of IoMT applications, extending beyond the traditional use cases to include emerging technologies such as UWB radar systems and DLT platforms; (2) an in-depth analysis of the integration of machine learning and AI in IoMT, highlighting innovative approaches in disease prediction and remote monitoring; (3) a detailed examination of privacy and security measures, proposing advanced cryptographic solutions and blockchain implementations to enhance data protection; and (4) the identification of future research directions, providing a roadmap for addressing current limitations and advancing the scientific understanding of IoMT in healthcare. By addressing current limitations and suggesting future research directions, this work aims to advance scientific understanding of the IoMT in healthcare.
Kouros Zanbouri, Mehdi Darbandi, Mohammad Nassr, Arash Heidari · 6 authors
Summary The latest developments in the industrial Internet of things (IIoT) have opened up a collection of possibilities for many industries. To solve the massive IIoT data security and efficiency problems, a potential approach is considered to satisfy the main needs of IIoT, such as high throughput, high security, and high efficiency, which is named blockchain. The blockchain mechanism is considered a significant approach to boosting data protection and performance. In the quest to amplify the capabilities of blockchain‐based IIoT, a pivotal role is accorded to the Glowworm Swarm Optimization (GSO) algorithm. Inspired by the collaborative brilliance of glowworms in nature, the GSO algorithm offers a unique approach to harmonizing these conflicting aims. This paper proposes a new approach to improve the performance optimization of blockchain‐based IIoT using the GSO algorithm due to the blockchain's contradictory objectives. The proposed blockchain‐based IIoT system using the GSO algorithm addresses scalability challenges typically associated with blockchain technology by efficiently managing interactions among nodes and dynamically adapting to network demands. The GSO algorithm optimizes the allocation of resources and decision‐making, reducing inefficiencies and bottlenecks. The method demonstrates considerable performance improvements through extensive simulations compared to traditional algorithms, offering a more scalable and efficient solution for industrial applications in the context of the IIoT. The extensive simulation and computational study have shown that the proposed method using GSO considerably improves the objective function and blockchain‐based IIoT systems' performance compared to traditional algorithms. It provides more efficient and secure systems for industries and corporations.
Blockchain technology has become a disruptive force in many different industries because it provides unparalleled security, transparency, and efficiency. In the context of cooperative networks, Blockchain's decentralized architecture provides a solid basis for enhancing trust, streamlining processes, and fostering innovation. This chapter examines how Blockchain can be used with cooperative networks and how it could fundamentally alter the way entities interact and communicate. Important areas of focus include Blockchain's technological foundations, applications in collaborative environments, and case studies that highlight its impacts. By examining the challenges and opportunities presented by this convergence, we intend to provide a comprehensive understanding of how Blockchain can revolutionize cooperative ecosystems. The field of scholarly communication is undergoing a significant transition due to technological advancements. This chapter looks at how blockchain technology and collaborative networks could alter contemporary living. We examine the basic shortcomings of the existing centralized model and discuss how the core concepts of immutability, transparency, and decentralization found in Blockchain technology can assist in resolving these problems. This paper explores the relationship between collaborative networks and blockchain technology. We start by outlining the fundamental ideas behind Blockchain technology and how it has developed. The use of Blockchain is then examined in a variety of cooperative settings, with its advantages and possible drawbacks discussed. We demonstrate the real-world effects of Blockchain-enabled collaborative networks across various industries with a number of case studies.
Abstract Blockchain technology has created a new software development context, with its own peculiarities, mainly due to the guarantees that the technology must satisfy, that is, immutability , distributability , and decentralization of data. Its rapid evolution over the last decade implied a lack of adequate verification tools, exposing developers and users to critical vulnerabilities and bugs. This paper clarifies the extent of block chain-oriented software (BoS), that goes well beyond smart contracts. Moreover, it provides an overview of the challenges related to software verification in the blockchain context, encompassing smart contracts, blockchain layers, cross-chain applications, and, more generally, BoS. This study aims to highlight the shortcomings of the state-of-art and of the state-of-practice of software verification in that context and identify, at the same time, new research directions.
The contemporary era experiences an unprecedented dependence on data generated by individuals via an array of interconnected devices constituting the Internet of Things (IoT). The information amassed through IoT devices serves many objectives, including prescriptive analytics and predictive maintenance, preemptive healthcare measures, disaster mitigation, operational efficiency, and increased yield. In contrast, most applications or systems that rely on user-generated data to fulfill their business objectives face challenges in adhering to privacy protocols. Consequently, users are exposed to many privacy risks. Such infringements upon privacy provisions give rise to apprehensions regarding the authenticity of the processed data. Hence, this paper presents weaknesses and challenges in current practices and proposes “PrivySeC,” a distributed ledger technology (DLT) based framework for privacy-preserving and secure sharing of personally and non-personally identifiable information. The security analysis indicates that the proposed solution ensures data privacy by design and complies with most of the requirements mandated by various privacy regulations. Similarly, PrivySeC promises low transaction latency and provides high throughput. Although we have created a privacy-preserving solution for sharing smart farm data, it can be customized to meet the specific privacy requirements of individual applications.
Hussein Ibrahim, Marwa A. Shouman, Nawal El‐Fishawy, Ayman Ahmed
Abstract Satellite swarm networks have occupied a prominent position in many modern applications due to their low cost, simplicity of design, and flexibility. Reliability is an influential factor in the design of satellite networks with different structures. Usually, small satellites are based on COST components, which may reduce continues operability due to the lack of using backup system on board the sagecraft. Any failure in one subsystem means a complete loss of the function and data stored in this subsystem; hence the need for a reliable and applicable solution for this matter is a crucial topic. Using the redundancy strategy in satellite swarm networks increases reliability and availability. Blockchain is characterized by using a distributed ledger which enables the database to be replicated across nodes in the network and results in increasing transparency, security, and trust. This paper suggests adoption of blockchain technology in distributed multi-satellite mission swarm networks to provide a high level of reliability and availability of the entire system; the blockchain is usually used to secure system transactions in multilayer approach by storage of the key parameters in more than one node; here we suggest the adoption of this approach not only to secure satellite network transaction, but also to increase system reliability so that failure of one node can be recovered by other nodes. We compared this approach with similar traditional networks that do not use blockchain. The results show a higher reliability efficiency of 95.3% for applying blockchain technology compared to 64.3% without the use of blockchain, as well as a higher availability of 99% compared to 91%.
The maritime industry has increasingly integrated advanced technologies such as AI, Blockchain, Big Data, and IoT, transforming traditional port operations into smart facilities aimed at enhancing global trade competitiveness. A particular focus has been on improving tracking and tracing services, with Blockchain technology emerging as pivotal for ensuring data integrity, transparency, and traceability across supply chains. This article proposes a blockchain-based tracking and tracing system model tailored for monitoring containers in Moroccan ports. Utilizing the Unified Modeling Language (UML), the model seeks to optimize resource allocation and boost stakeholder satisfaction through detailed diagrams and functional data requirements depiction. Despite challenges such as IoT terminal platform connectivity and operator resitance, successful implementation was achieved, establishing a foundational framework for a comprehensive container monitoring system. This model provides valuable insights for supply chain professionals and scholars interested in item tracking, aiming to integrate Blockchain with technologies like RFID, GPS, RTLS, QR Codes, BLE, and IoT sensors to enhance port operation efficiency and container management effectiveness. By leveraging these integrated technologies, ports can further improve operational efficiency and ensure accurate traceability of containers throughout the supply chain, contributing to overall trade facilitation and economic growth
Seyed Mojtaba Hosseini Bamakan, Saeed Banaeian Far
The fourth industrial revolution has significantly increased the adoption of Digital Twins (DTs) across various sectors, including intelligent manufacturing, automation, logistics, and medical analysis. Despite substantial progress in deploying DT projects, numerous challenges remain, such as managing distributed data flows, protecting commercial confidentiality, securing intellectual property, and ensuring privacy and security. This research introduces a novel approach to addressing these challenges by leveraging blockchain and Web3 technologies, including non-fungible tokens (NFTs) and Distributed Autonomous Organizations (DAOs). The study aims to develop a distributed, tamper-proof DT cooperation platform that facilitates traceable and trustworthy data sharing while preserving intellectual property rights and enabling decentralized governance. This platform enhances idea and invention ownership, promotes collective decision-making through consensus protocols, and explores innovative solutions like blockchain-based federated learning and efficient DT project fundraising tools. Relying on security models and analysis tools, this study addresses several important security analysis methods/tools/models (e.g., random oracle model, BAN logic, AVISPA tool, and TAMARIN prover) that are known as practical analysis methods. They can strongly prove every claimed security feature of DT projects. The proposed solutions set the stage for future academic and industrial advancements, supported by a comprehensive SWOT (Strongness - Weakness - Opportunity - Threat) analysis, and outline potential future research directions.
Salah Hamza Alharbi, Ali Musa Alzahrani, Toqeer Ali Syed, Saad Said Alqahtany
Remote healthcare monitoring (RHM) has become a pivotal component of modern healthcare, offering a crucial lifeline to numerous patients. Ensuring the integrity and privacy of the data generated and transmitted by IoT devices is of paramount importance. The integration of blockchain technology and smart contracts has emerged as a pioneering solution to fortify the security of internet of things (IoT) data transmissions within the realm of healthcare monitoring. In today’s healthcare landscape, the IoT plays a pivotal role in remotely monitoring and managing patients’ well-being. Furthermore, blockchain’s decentralized and immutable ledger ensures that all IoT data transactions are securely recorded, timestamped, and resistant to unauthorized modifications. This heightened level of data security is critical in healthcare, where the integrity and privacy of patient information are nonnegotiable. This research endeavors to harness the power of blockchain and smart contracts to establish a robust and tamper-proof framework for healthcare IoT data. Employing smart contracts, which are self-executing agreements programmed with predefined rules, enables us to automate and validate data transactions within the IoT ecosystem. These contracts execute automatically when specific conditions are met, eliminating the need for manual intervention and oversight. This automation not only streamlines the process of data processing but also enhances its accuracy and reliability by reducing the risk of human error. Additionally, smart contracts provide a transparent and tamper-proof mechanism for verifying the validity of transactions, thereby mitigating the risk of fraudulent activities. By leveraging smart contracts, organizations can ensure the integrity and efficiency of data transactions within the IoT ecosystem, leading to improved trust, transparency, and security. Our experiments demonstrate the application of a blockchain approach to secure transmissions in IoT for RHM, as will be illustrated in the paper. This showcases the practical applicability of blockchain technology in real-world scenarios.
Logistics Management Systems (LMS) are crucial to global supply chains, ensuring efficient planning, data analysis and control of various logistics management processes. However, traditional LMS face complex challenges in mitigating cyber threats and data breaches. Blockchain technology emerges as a revolutionary solution, equipping LMS with traceability, immutability, and anonymity. While previous solutions focus on blockchain's theoretical potential or its application to singular aspects of logistics such as goods tracking or auction facilitation, our proposed Decentralized Logistics Management System (DLMS) distinguishes itself in two ways: first, driven by practical insights, we investigate the concurrent challenges and the advantages of blockchain that can be integrated into industrial LMS; second, we design a blockchain-based Decentralized Logistic Management System (DLMS) that includes comprehensive functional modules, including identity authentication, fair bidding mechanisms, and goods tracking. Finally, we implement a prototype of our proposed system and deploy the prototype on the Ethereum testnet to evaluate the performance of the proposed architecture. The experimental findings demonstrate the efficiency of our system and its potential as an effective solution to the identified challenges.
In the context of the rapid development of Internet of Things (IoT) technology and the extensive proliferation of the global Internet, the authenticity of data has become a focal point of societal demand. It plays a decisive role in enhancing the quality of decision-making and operational efficiency. However, the storage and authenticity verification of large-scale IoT real-time data present unprecedented technical challenges. Faced with the inherent data security risks of traditional centralized cloud storage, blockchain technology reveals its unique potential for solutions with its inherent immutability and decentralization. Nevertheless, current blockchain-based data storage solutions are still restricted by high costs and inefficiency. To address these challenges, this paper innovatively proposes the BI-TSFID framework, which leverages the benefits of Ethereum and IPFS and optimizes the Merkle Tree structure and verification mechanisms. The BI-TSFID framework adopts a strategy of on-chain data summary storage and off-chain computation. This approach provides IoT with efficient and reliable data storage, reduces operational costs, and simplifies the verification process. This research has improved the data computation efficiency by refining the structure of the Merkle Tree and analyzed its optimal branch number. Additionally, the study introduces a sampling-based data integrity verification method that significantly reduces resource consumption during the verification process. Experimental results show that the solutions proposed in this paper effectively enhance the efficiency and security of IoT data management and provide valuable guidance for the theory and practice of real-time data storage and verification, further promoting the development and innovation in the related technological fields.
Harun Jamil, Yang Jian, Faisal Jamil, Mohammad Hijjawi · 5 authors
This article explores integrating digital twin technology and blockchain within smart grids to optimize energy trading among prosumers and consumers in smart nanogrids. Our platform employs a multi-objective optimization strategy , including Particle Swarm Optimization (PSO), to delineate energy trading routes between nanogrids, optimizing parameters such as route distance, surplus renewable energy, and energy power loss. Our platform ensures efficient and effective energy trading services by meticulously considering factors such as surplus energy amount, energy price, route distance, and time. The proposed digital twin-based architecture comprises seven layers, each tailored to address specific functionalities and services for energy management within smart nanogrids. At the apex lies the application layer (digital twin services), leveraging the digital twin's capabilities to optimize energy trading, manage surplus energy, and efficiently meet energy demand. This layer facilitates informed decision-making and resource optimization. Integrating a digital twin-driven architecture with a blockchain-based platform tackles challenges inherent in decentralized energy trading. The digital twin offers real-time energy resource monitoring and optimisation, ensuring efficient utilisation and autonomous decision-making. Concurrently, leveraging blockchain technology ensures secure and transparent transactions, fostering trust among participants and facilitating peer-to-peer energy exchange. Task generation, device virtualization , task mapping, scheduling on edge devices, and task assignment layers further streamline task execution and resource utilization , enhancing the efficiency of energy management processes. The predictive optimal energy control layer also orchestrates the entire architecture, enabling predictive and optimized energy control within smart nanogrids. Furthermore, the Security as a Service (SECaaS) layer enhances security and trustworthiness using blockchain technology, incorporating components such as consensus management, real-time distributed ledgers , and identity management. This layer enhances the security and transparency of energy-related transactions and data within the digital twin framework. The results showcase a remarkable 53% reduction in peak load, emphasizing the optimized energy consumption and demand achieved. Furthermore, our platform has significantly increased the utilization of renewable energy resources by 24%, highlighting its contribution to sustainable energy resource management. Rigorous assessment of the prediction and optimization modules reveals their high accuracy and precision, with mean absolute percentage error (MAPE) values of 15.125 and 14.369, respectively. These findings underscore the efficacy and reliability of our digital twin-based approach, surpassing existing solutions and benchmarks.
Mwaffaq Abu AlHija, Osama Al-Baik, Abdelrahman H. Hussein, Hikmat A. M. Abdeljaber
The adoption of blockchain technology provides significant disruptive benefits to internet-of-things (IoT) applications in healthcare in vital aspects like security, integrity, transparency, and efficiency. Nevertheless, in order to fully realize the potential of blockchain-driven solutions, healthcare organizations have to address intricate compromises between essential factors including scalability, privacy and resource utilization considering that the data sensitivity alongside strict regulatory compliance requirements characterize this sector. This research discusses the fundamental aspects of these trade-offs, including the range of consensus protocols (e.g. proof-of-work, proof-of-stake) and cryptographic techniques (e.g. zero-knowledge proofs, homomorphic encryption). A systematic choice matrix is created, which relates specific use cases of the healthcare IoT to the optimal tailored blockchain structures on such critical metrics as transaction volume, frequency, privacy level and resource restrictions. The suggested framework provides solid, actionable recommendations to healthcare organizations in order to help them benefit from the enormous promise of the blockchain for connected IoT healthcare by finding a balance between decentralization advantages and performance, security and compliance requirements.
Blockchain is a technology that is rapidly gaining prominence and finding applications in various sectors such as banking, supply chain, healthcare, and e-governance. The consensus algorithm employed in a blockchain network is crucial as it directly impacts the network's performance and security. Different consensus techniques exist, including Proof of Work (PoW), Proof of Stake (PoS), Robust Proof of Stake (RPoS), and Delegate Proof of Stake (DPoS), each with its own set of advantages and disadvantages. In this work, we propose a new consensus algorithm called Delegated Proof of Stake with Exponential Back-off (DPoSEB). DPoSEB utilizes a stake-based selection of delegates and employs an exponential back-off technique to mitigate collisions among nodes within the network. Each delegate is assigned a random sleep time, and the node with the shortest wake-up time is chosen to mine the block for that particular round. However, collisions among nodes can still occur. To provide a fair chance for each delegate node, collided nodes are assigned an exponential back-off time. We implement our proposed algorithm on an Ethereum-based private blockchain network. To evaluate the effectiveness of our proposed work, we compare it with existing consensus mechanisms such as PoS (version 2) and Delegated RPOS with downgrading (DDRPOS) using different scenarios in terms of transaction latency, waiting time, and fairness as evaluation metrics. The results reveal that DPoSEB performs better than POS and DDRPOS.
This study introduces the Distributed Drone Reputation Management (DDRM) framework, designed to fortify trust and authenticity within the Internet of Drone Things (IoDT) ecosystem. As drones increasingly play a pivotal role across diverse sectors, integrating crowdsourced drone services within the IoDT has emerged as a vital avenue for democratizing access to these services. A critical challenge, however, lies in ensuring the authenticity and reliability of drone service reviews. Leveraging the Ethereum blockchain, DDRM addresses this challenge by instituting a verifiable and transparent review mechanism. The framework innovates with a dual-token system, comprising the Service Review Authorization Token (SRAT) for facilitating review authorization and the Drone Reputation Enhancement Token (DRET) for rewarding and recognizing drones demonstrating consistent reliability. Comprehensive analysis within this paper showcases DDRM's resilience against various reputation frauds and underscores its operational effectiveness, particularly in enhancing the efficiency and reliability of drone services.
Abstract Decentralized autonomous organization (DAO)-based applications can revolutionize traditional centralized decision-making procedures and services by enabling scalable, decentralized, autonomous, and democratized decision-making processes. Unlike traditional applications, DAO-based decentralized applications use Ethereum blockchain-based smart contract programs to execute policies or make automated decisions. To that end, 6 G technologies can improve the latency and reliability of many existing blockchain-based DAOs. Previous research did not investigate the execution of DAO and non-DAO-based applications, as well as an adaptive resource choreography scheme, while accounting for various 6 G technologies, blockchain, and mobile-edge cloud (MEC). To prevail over the previous shortcomings, this article supplies a street smart multi-platform coordination, application scheduling, and low-latency-aware resource choreography scheme for both DAO and non-DAO-based application execution over blockchain and MEC-enabled 6 G networks by taking heterogenous DAO and non-DAO application count, application requirements, physical worker, virtual worker, and communication resource status into account. The results verified that the proposed kaizen scheme delivers at least 11.26% app work completion delay gain, 7.2% user energy overhead gain, 6.55% user economic charge gain, and 21% service provider profit than the compared schemes.
Muhammad Faheem, Basit Raza, Muhammad Shoaib Bhutta, Syed Hamid Hussain Madni
Abstract The rapid and green energy transition is essential to deal with the fast‐growing energy needs in both public and industrial sectors. This has paved the way to integrate distributed renewable energy resources () such as solar, hydro, wind, and geothermal into the power grid (). Wind and solar are free, zero‐carbon emission, and everlasting power sources that contribute 5% and 7% of global electricity generation, respectively. Therefore, the fast, secure, and reliable integration of these green is critical to achieve the instant energy demands. Smart grid due to inherited characteristics such as intelligent sensing, computing, and communication technologies can effectively integrate the . However, the existing smart grid communication architecture faces various cyberattacks, resulting in poor integration, monitoring, and control of . In this respect, blockchain technology can provide fast, secure, and efficient end‐to‐end communication between in the smart grid. In this study, the authors propose a blockchain‐based resilient and secure scheme called for wireless sensor networks ‐based events monitoring and control in . Experimental studies and performance analyses are carried out to predict the efficiency of the proposed scheme by considering numerous standard metrics. The extensive numerical results demonstrated that the proposed scheme is significant in terms of secure, resilient, and reliable information transmission for in .
BACKGROUND: Telehealth played a critical role during the COVID-19 pandemic and continues to function as an essential component of health care. Existing platforms cannot ensure privacy and prevent cyberattacks. OBJECTIVE: The main objectives of this study are to understand existing cybersecurity issues in identity management and trustworthy communication processes in telehealth platforms and to design a software architecture integrated with blockchain to improve security and trustworthiness with acceptable performance. METHODS: We improved personal information security in existing telehealth platforms by adopting an innovative interdisciplinary approach combining design science, social science, and computer science in the health care domain, with prototype implementation. We used the design science research methodology to implement our overall design. We innovated over existing telehealth platforms with blockchain integration that improves health care delivery services in terms of security, privacy, and efficiency. We adopted a user-centric design approach and started with user requirement collection, followed by system functionality development. Overall system implementation facilitates user requirements, thus promoting user behavior for the adoption of the telehealth platform with decentralized identity management and an access control mechanism. RESULTS: Our investigation identified key challenges to identity management and trustworthy communication processes in telehealth platforms used in the current health care domain. By adopting distributed ledger technology, we proposed a decentralized telehealth platform to support identity management and a trustworthy communication process. Our design and prototype implementation using a smart contract-driven telehealth platform to provide decentralized identity management and trustworthy communication with token-based access control addressed several security challenges. This was substantiated by testing with 10,000 simulated transactions across 5 peers in the Rahasak blockchain network. The proposed design provides resistance to common attacks while maintaining a linear time overhead, demonstrating improved security and efficiency in telehealth services. We evaluated the performance in terms of transaction throughput, smart contract execution time, and block generation time. To create a block with 10,000 transactions, it takes 8 seconds on average, which is an acceptable overhead for blockchain-based applications. CONCLUSIONS: We identified technical limitations in current telehealth platforms. We presented several design innovations using blockchain to prototype a system. We also presented the implementation details of a unique distributed architecture for a trustworthy communication system. We illustrated how this design can overcome privacy, security, and scalability limitations. Moreover, we illustrated how improving these factors sets the stage for improving and standardizing the application and for the wide adoption of blockchain-enabled telehealth platforms.
Haya R. Hasan, Mohammad Madine, Ahmad Musamih, Raja Jayaraman · 7 authors
Recent years have witnessed the emergence of digital twins in the industrial metaverse, significantly transforming sectors such as manufacturing, automotive, oil and gas, and gaming. As a result, these sectors have experienced increased efficiency, innovation, and revolutionary solutions. Non-fungible tokens (NFTs) have the potential to enhance digital twins in the industrial metaverse by offering opportunities for monetization, traceability, and tracking. Moreover, NFTs can reshape the way industries operate by providing superior transparency, asset management, and intellectual property protection. This paper explores the potential of different types of NFTs, including dynamic and composable NFTs, in various applications within the industrial metaverse that heavily relies on digital twins. We present various industrial use cases where NFTs play a major role. Specifically, we design, implement, and test two use cases involving dynamic and composable NFTs. The data processing methods include algorithm development, simulation, and empirical testing within the industrial metaverse framework. Finally, we identify open research areas and future directions for the industrial metaverse.