The world is undergoing a profound transformation with the advent of intelligent information era. 6G networks envisioned being the game changer in next generation wireless communication systems that will address the challenges of limited information speed escalated with the augmentation of billions of data applications encountered by the current fifth generation (5G) networks. Some key radical technologies in 6G together with existing 5G candidate schemes will guarantee the expected quality of experience (QoE) to attain ubiquitous wireless connectivity for the Internet of Everything (IoE) ranging from the telecom industry to digital smart industries. Blockchain technology (BCT) has gained significant attention due to undertake the decentralization, transparency, spectrum resource scarcity, inherent privacy and security, poor interoperability, confidentiality, and emerging smart applications domains including Industrial IoT and Industry 4.0. The mismatch between the requirements of many data intensive disruptive IoT applications and 5G network capabilities steered the demand of decentralized BCT based 6G architecture. Inspired by these facts, this paper studies an extensive survey to draw a new direction of blockchain integration into 6G mobile networks, IoT technologies, and smart industries focusing the potential merits and challenges in terms of infrastructure sharing, computational loads, latency, bandwidth overhead, business model, sustainability goals, and edge intelligence. We highlighted the convergence of IoT in blockchain to enable intelligent distribution in future industrial IoT and the technical model of 6G networks to realize the successful deployment of BCT schemes. This paper pointed out the current intriguing challenges, canvassed the mitigation techniques, and plausible future research opportunities that may benefit the pursuit of this vision.
In this paper, we deal with questions related to blockchains in complex Internet of Things (IoT)-based ecosystems. Such ecosystems are typically composed of IoT devices, edge devices, cloud computing software services, as well as people, who are decision makers in scenarios such as smart cities. Many decisions related to analytics can be based on data coming from IoT sensors, software services, and people. However, they are typically based on different levels of abstraction and granularity. This poses a number of challenges when multiple blockchains are used together with smart contracts. This work proposes to apply our concept of elasticity to smart contracts and thereby enabling analytics in and between multiple blockchains in the context of IoT. We propose a reference architecture for Elastic Smart Contracts and evaluate the approach in a smart city scenario, discussing the benefits in terms of performance and self-adaptability of our solution.
The development of information and communication technology in terms of sensor technologies cause the Internet of Things (IoT) step toward smart homes for prevalent sensing and management of resources. The gateway connections contain various IoT devices in smart homes representing the security based on the centralized structure. To address the security purposes in this system, the blockchain framework is considered a smart home gateway to overcome the possible attacks and apply Deep Reinforcement Learning (DRL). The proposed blockchain-based smart home approach carefully evaluated the reliability and security in terms of accessibility, privacy, and integrity. To overcome traditional centralized architecture, blockchain is employed in the data store and exchange blocks. The data integrity inside and outside of the smart home cause the ability of network members to authenticate. The presented network implemented in the Ethereum blockchain, and the measurements are in terms of security, response time, and accuracy. The experimental results show that the proposed solution contains a better outperform than recent existing works. DRL is a learning-based algorithm which has the most effective aspects of the proposed approach to improve the performance of system based on the right values and combining with blockchain in terms of security of smart home based on the smart devices to overcome sharing and hacking the privacy. We have compared our proposed system with the other state-of-the-art and test this system in two types of datasets as NSL-KDD and KDD-CUP-99. DRL with an accuracy of 96.9% performs higher and has a stronger output compared with Artificial Neural Networks with an accuracy of 80.05% in the second stage, which contains 16% differences in terms of improving the accuracy of smart homes.
Sukhpal Singh Gill, Ricardo Vinuesa, Venki Balasubramanian, Soumya K. Ghosh
We are pleased to present a special issue that focuses on the software systems for managing the impact of the coronavirus disease 19 (COVID-19) pandemic. The COVID-19 pandemic has affected around 192 million people worldwide and has led to Ë4.13 million deaths as of July 22, 2021. Globally, most of the countries have implemented lockdowns to protect their citizens. However, lockdown over an extended period is unsustainable. Hence, it is widely believed that virus testing and tracking is the best approach to ease lockdown measures. There is a need for innovative software systems to manage the impact of the COVID-19 pandemic effectively in many areas such as healthcare system, transport systems, supply-chain system, educational system, government-service delivery, pharmaceutical companies, manufacturing, software industries, and multinational companies. For example, in healthcare, smart-software systems would be able to remotely measure a person's body temperature, heart and respiratory rates, identifying their movements (including sneezing, coughing, shivering, etc.) to identify whether a person is displaying symptoms of COVID-19 or not. An essential aspect associated with these technologies is data privacy, scalability, and quality of service (QoS) in terms of reliability, availability, security, latency, and energy which need to be considered throughout the development of the software systems. In countries like India, UK, Russia, Brazil, and USA, the system would also help to ensure that isolated communities have access to testing, delivered in a fast, accurate, and efficient manner. These software systems would help and support the assessment of public-health strategies and policies such as social distancing and assess further interventions to control the spread of the virus. Innovative software systems can increase stakeholder participation, as cost-effective assistance in the COVID-19 pandemic monitoring is of great interest to many countries. To manage the impact of this pandemic, there is a need to design and develop scalable, reliable, and energy-efficient sustainable software solutions for different COVID-19 scenarios. In consideration of the existing systems and their features, an Internet of Things (IoT)-based system suitable for COVID-19 or pandemic situations associated with other influenza viruses can be developed. Furthermore, these systems can be integrated with artificial-intelligence (AI) processes for effective data-collection, analysis, statistical visualization, sharing, and decision making. Moreover, these systems can be implemented using both simulations and real-time testbeds for COVID-19 operations (sanitization, medication, monitoring, thermal imaging, etc.) to test their performance in terms of scalability, reliability, availability, and energy efficiency. There is a need to use AI methods, such as reinforcement learning, deep learning, and genetic algorithms while developing IoT-based software systems to achieve self-learning, self-adaptation, and autonomous decision-making capabilities in order to improve efficiency of the systems. Meanwhile, a huge voluminous amount of complex data is generated from various sources including World Health Organization (WHO), social networking, edge devices, private and public hospitals, patients and academic institutes, which needs an effective big data analytics mechanism to manage this data proficiently. Furthermore, there is a need to study the impact of system configuration on workload processing at different cloud nodes while maintaining the QoS dynamically. The data are collected in databases, it is subsequently examined and monitored, and it is important to manage data consistency and integrity. In this context, we argue that it is essential to employ decentralized data-gathering approaches, maintaining the privacy of the population as a high priority. This special issue has received articles by researchers and practitioners from both academia and industry to develop innovative software systems for managing the impact of the COVID-19 pandemic. This special issue, therefore, aims to focus the attention of its readers to four research articles carefully selected after multiple rounds of peer-review. The brief contributions of these papers are discussed in the following section: The first paper entitled âAn approach to forecast impact of COVID-19 using supervised machine learning modelâ by Mohan et al.1 proposes a hybrid model to predict the effect of COVID-19 using moving regressive, autoregressive, and ensemble learning model. This work uses two datasets from Worldometer and Ministry of Health & Family Welfare of India to conduct the countrywise predictions across the world and statewise predictions of India, respectively. The second paper entitled âNovidChain: Blockchain-based privacy-preserving platform for COVID-19 test/vaccine certificatesâ by Abid et al.2 includes various promising ideas such as maintains the immutability and data integrity using Blockchain technology, enhances the privacy by incorporating encryption for personal information and verifies the COVID-19 proof using W3C verifiable credentials standard immediately. The third paper entitled âSoftware System to Predict the Infection in COVID-19 Patients using Deep Learning and Web of Thingsâ by Singh et al.3 generates synthetic data using various data augmentation techniques. Proposed system uses U-Net and WoT to segment the COVID Medseg and Radiopedia datasets in an autonomic manner. Experimental results show that the system gives better performance in terms of network latency, response time, and server latency. The fourth paper entitled âAdvanced Data Integration in Banking, Financial, and Insurance Software in the Age of COVID-19â by Maiti et al.4 contributes to recognize the effect of the COVID-19 pandemic on the global Banking Financial Services and Insurance landscape. Further, a hype cycle has been developed to find out the important software technologies to handle real-world challenges related to corporate. We believe the work that has been approved in this special issue will assist readers of the journal and a broader research community to learn about the topics of software systems and impacts of COVID-19 pandemic, and inspire them to study more in this area. We would like to express our gratitude to the Editor-in-Chief (Prof. Rajkumar Buyya) and editorial board members for allowing us to bring out this special issue and guiding us throughout the process. We also want to express our gratitude to and further acknowledge the administrative staff, reviewers, and especially the authors for their contributions to the success of this issue.
Internet of Things (IoT) applications are becoming more integrated into our society and daily lives, although many of them can expose the user to threats against their privacy. Therefore, we find that it is crucial to address the privacy requirements of most of such applications and develop solutions that implement, as far as possible, privacy by design in order to mitigate relevant threats. While in the literature we may find innovative proposals to enhance the privacy of IoT applications, many of those only focus on the edge layer. On the other hand, privacy by design approaches are required throughout the whole system (e.g., at the cloud layer), in order to guarantee robust solutions to privacy in IoT. With this in mind, we propose an architecture that leverages the properties of blockchain, integrated with other technologies, to address security and privacy in the context of IoT applications. The main focus of our proposal is to enhance the privacy of the users and their data, using the anonymisation properties of blockchain to implement user-controlled privacy. We consider an IoT application with mobility for smart vehicles as our usage case, which allows us to implement and experimentally evaluate the proposed architecture and mechanisms as a proof of concept. In this application, data related to the user's identity and location needs to be shared with security and privacy. Our proposal was implemented and experimentally validated in light of fundamental privacy and security requirements, as well as its performance. We found it to be a viable approach to security and privacy in IoT environments.
Federico Daidone, Barbara Carminati, Elena Ferrari
The Internet of Things (IoT) pervades our lives every day and has given end users the opportunity of accessing personalized and advanced services based on the analysis of the sensed data. However, IoT services are also characterized by new challenges related to security and privacy because end users often share sensitive data with different consumers without precise knowledge of how they will be managed and used. To cope with these issues, we propose a blockchain-based privacy enforcement framework where users can define how their data can be used and check if their will is respected without relying on a centralized manager. The preliminary tests we performed, simulating different scenarios, show the feasibility of our approach.
Andreas Heider-Aviet, Danny Roswin Ollik, Stefano Berlato, Silvio Ranise · 9 authors
Providing seamless connectivity and services across national borders are intricate challenges with multifarious underlying aspects, ranging from the network management to business and political considerations. Since the cross-border inter-Public Land Mobile Network (PLMN) network handover is currently not available in European cellular networks, we present a complementary approach, diminishing the connectivity gap to a minimum. By leveraging Distributed Ledger Technology (DLT), we establish a dynamic, secure data exchange and management solution between several Mobile Network Operators (MNOs) of different countries. Systematically integrating foreign cell and base station parameter (i.e., Radio Access Network (RAN) data) of border regions into the internal network management systems permits their usage in standardized Mobility Management procedures. We demonstrate that this type of collaboration on the inter-MNO network governance considerably improves the network quality and customer experience when crossing national borders. Since foreign RAN data is also required for the inter-PLMN network handover (and can serve many additional purposes) and provided that our solution is not relying on any specific mobile network technology generation (e.g., 4G or 5G), we conclude that it is a fundamental step towards an inter-MNO ecosystem beyond 5G.
Smart contracts provide computation facilities to blockchains, enabling many application scenarios where automatic analysis and complex transactions can be performed. However, in situations where the flow of information is variable and there are time, quality, and/or cost constraints imposed, smart contracts do not usually offer enough performance. In this article, we describe an elasticity framework that enables dynamic adaptation of smart contracts with respect to used resources, analytics quality, and incurred costs in a transparent manner for both smart contract developers and users. We validate our framework in an Internet of Things and Smart City scenario where several analytics are computed using Elastic Smart Contracts that dynamically adapt the appropriate elasticity variables.
Traditional data collection, storage and processing of Electronic Health Records (EHR) utilize centralized techniques that pose several risks of single point of failure and lean the systems to a number of internal and external data breaches that compromise their reliability and availability. Blockchain is an emerging distributed technology that can solve these issues due to its immutability and architectural nature that prevent records manipulation or alterations. In this paper, we discuss the progress and opportunities of remote patient monitoring using futuristic blockchain technologies and its two primary frameworks: Ethereum and Hyperledger Fabric. We also discuss the possible blockchain use cases in software engineering for systematic, disciplined, and quantifiable application development. The study extends by introducing a system architecture for EHR data management using Ethereum as a model. We discuss the challenges and limitations along with the initial evaluation results of the proposed system and draw future research directions in this promising area.
Chenchen Tan, Xinghao Li, Tom H. Luan, Bruce Gu · 6 authors
With the evolving Internet of Vehicles (IoVs), the onboard resources of vehicles in computing and communication are experiencing fast growth. The sharing of road information and computing results among vehicles in proximity can effectively improve the utility of IoVs. However, remote inter-vehicular resource sharing, e.g., information and computing resource sharing, remains an under-explored issue. Motivated by this, we propose a novel digital twin based fair trading platform built upon consortium blockchain to enable city-wide vehicular resource sharing. Specifically, we first develop a digital twin based vehicular platform to enable vehicular resource sharing in the cloud. To track and secure the resource sharing among digital twins, the consortium blockchain is deployed, which is enforced by the designed smart contracts with an efficient Proof-of-Stake (PoS) consensus algorithm. In addition, an innovative incentive mechanism is devised to motivate the city-wide resource sharing for vehicles, which can maximize the profits of task publishers. Using extensive evaluations, we show the effectiveness of the proposed system.
Recently, serious damages have occurred in e-commerce applications due to rapidly increasing data leaks and end-user vulnerabilities. Although the source of the vulnerabilities is different, attacks result in the theft of unsafe data. In particular, the theft of credit card information reveals a financial loss. In this study, a blockchain-based secure storage model has been developed in order to prevent the theft of credit card information in e-commerce applications as a result of a possible data leak. In the sample e-commerce application developed with ASP.NET, data other than credit cards are stored. Credit card data is transmitted to the blockchain over the API with SSL protection in the e-commerce application. The blockchain model was developed using MongoDB with the BigchainDB framework. The data in each block of the blockchain is encrypted with Advanced Encryption Standard (AES) 256 bits. The data integrity of the block is provided by the SHA256 algorithm. it is aimed to protect credit card data from a possible data leak with the proposed BigchainDB-based blockchain model.
Today, Data Driven Marketing is challenged by the supply of vague data, inconsistencies between them and fraud through advertising in the digital marketing ecosystem.Through three basic concepts like open ledger, distributed ledger, and miners, BlockChain (BC) is a perfectly positioned technology, restoring not only trust and transparency, but ensuring a greater uniformity of transactions within a largely fragmented sector.BC makes DDM more directly and reliable, validating and analyzing each customer's movement in advertising campaigns.In BlockChain the traditional principle that creates the positive correlation between fee and delivery time through the "Third Trust Party" becomes null because transparency is one of the basic properties of this technology, which on the other hand for DDM is the Achilles heel.
The Internet of Things (IoT) and Blockchain distribution ledger technology as a concept is enchanting facilities and industrial developments with advanced implements in many applications. The IoT and Blockchain market is further expected to develop three times from current development by 2025. Though many IoT applications have major challenges in safest data transaction and scalability issues while increasing the number of IoT devices. Practical Byzantine Fault Tolerance (PBFT) is a widely used form of decentralized consent, however the network node's confidence in PBFT cannot be guaranteed, as well as the mechanism of reaching consensus will consume a large amount of network services. The article suggests the novel consensus process, which is referred to a Hybrid consensus blockchain algorithm and control authentication on Trust. The Internet of Things applications are integrated with a blockchainbased decentralized system that authenticates the IoT devices through distributed control authentication. This hybrid consensus blockchain method provides security for transactions and access to unauthorized devices is restricted. The PBFT algorithm using a decentralized network system using blockchain has no restriction of IoT devices. Even malicious users create the grouping into the network that has been controlled by the distributed control authentication method. Further then malicious users are rejected from the decentralized network. In this paper, we propose the Hybrid consensus blockchain and PBFT algorithm ensure the safest data transaction through blockchain technology and improves the performance of the decentralized network. Finally, we have presented a Hybrid Consensus algorithm to be utilized in the PBFT method which enables the safest data transaction.
Blockchain is a type of decentralized distributed network which acts as an immutable digital ledger. Despite the absence of any central governing authority to validate the blocks in the ledger, it is considered secure and immutable due to the consensus protocol among various nodes of the network. A consensus algorithm is a mechanism that guarantees the reliability of the blockchain and helps all connected nodes or peers to reach common ground regarding the present state of the blockchain network thus an ideal consensus algorithm must be secure, reliable, and fast. There are several different algorithms to reach a consensus among the nodes thus this article seeks to test the practicality of Proof of Authority in the blockchain network as a consensus algorithm and its comparison with current mainstream consensus algorithms.
Muyideen Omuya Momoh, P.U. Chinedu, Wilson Nwankwo, Daniel Aliu · 5 authors
In recent times, more scholastic and social attention have been paid to blockchain and its distributed ledger system mechanism. The reasons for this ever-increasing attention cannot be far-fetched: blockchain now occupies a copious position in the present-day ways of doing things economically, digitally and âdigital-sociallyâ. Blockchain could be described as a distributed ledger system that allows secure transactions without a central management system. In this distributed ledger system, transactions are coded into blocks, which are linked to each other in the form of a chain. The first application of blockchain is in the bitcoin cryptocurrency. Though not limited to bitcoin, blockchain finds usefulness in security and trusts for instance, digital assets could be coded into blocks to ensure and enforce quality of trust. Consequent upon the quality of trust the blockchain confers on a digital asset, transparency among participating nodes is guaranteed. This is because, any change made to any record in a given block automatically initiates and enforces a corresponding change in all other blocks in the chain hence tampering or breach is almost impossible. Owing to its impressive prospects in the socioeconomic and political ecosystem, this paper was conceived to examine the current developments around this novel technology with particular emphasis on its benefits and proposed challenges and needs to fill the gap created in the vital socioeconomic domains. The paper concludes that the blockchain technology is a plausible approach to restoring the trust, confidentiality, availability and integrity in transactions in the cyberspace and the world at large as majority of the global economy thrives in the cloud.
Houshyar Honar Pajooh, Mohammad A. Rashid, Fakhrul Alam, Serge Demidenko
Abstract The diversity and sheer increase in the number of connected Internet of Things (IoT) devices have brought significant concerns associated with storing and protecting a large volume of IoT data. Storage volume requirements and computational costs are continuously rising in the conventional cloud-centric IoT structures. Besides, dependencies of the centralized server solution impose significant trust issues and make it vulnerable to security risks. In this paper, a layer-based distributed data storage design and implementation of a blockchain-enabled large-scale IoT system are proposed. It has been developed to mitigate the above-mentioned challenges by using the Hyperledger Fabric (HLF) platform for distributed ledger solutions. The need for a centralized server and a third-party auditor was eliminated by leveraging HLF peers performing transaction verifications and records audits in a big data system with the help of blockchain technology. The HLF blockchain facilitates storing the lightweight verification tags on the blockchain ledger. In contrast, the actual metadata are stored in the off-chain big data system to reduce the communication overheads and enhance data integrity. Additionally, a prototype has been implemented on embedded hardware showing the feasibility of deploying the proposed solution in IoT edge computing and big data ecosystems. Finally, experiments have been conducted to evaluate the performance of the proposed scheme in terms of its throughput, latency, communication, and computation costs. The obtained results have indicated the feasibility of the proposed solution to retrieve and store the provenance of large-scale IoT data within the Big Data ecosystem using the HLF blockchain. The experimental results show the throughput of about 600 transactions, 500 ms average response time, about 2â3% of the CPU consumption at the peer process and approximately 10â20% at the client node. The minimum latency remained below 1 s however, there is an increase in the maximum latency when the sending rate reached around 200 transactions per second (TPS).
Desire Ngabo, Dong Wang, Celestine Iwendi, Joseph Henry Anajemba · 6 authors
The recent developments in fog computing architecture and cloud of things (CoT) technology includes data mining management and artificial intelligence operations. However, one of the major challenges of this model is vulnerability to security threats and cyber-attacks against the fog computing layers. In such a scenario, each of the layers are susceptible to different intimidations, including the sensed data (edge layer), computing and processing of data (fog (layer), and storage and management for public users (cloud). The conventional data storage and security mechanisms that are currently in use appear to not be suitable for such a huge amount of generated data in the fog computing architecture. Thus, the major focus of this research is to provide security countermeasures against medical data mining threats, which are generated from the sensing layer (a human wearable device) and storage of data in the cloud database of internet of things (IoT). Therefore, we propose a public-permissioned blockchain security mechanism using elliptic curve crypto (ECC) digital signature that that supports a distributed ledger database (server) to provide an immutable security solution, transaction transparency and prevent the patient records tampering at the IoTs fog layer. The blockchain technology approach also helps to mitigate these issues of latency, centralization, and scalability in the fog model.
Mohamed Elhoseny, Khalid Haseeb, Asghar Ali Shah, Irshad Ahmad · 6 authors
Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable services in emerging fields. An IoT-based healthcare solution facilitates patients, hospitals, and professionals to observe real-time and critical data. In the literature, most of the solution suffers from data intermission, high ethical standards, and trustworthiness communication. Moreover, network interruption with recurrent expose of sensitive and personal health data decreases the reliance on network systems. Therefore, this paper intends to propose an IoT solution for AI-enabled privacy-preserving with big data transferring using blockchain. Firstly, the proposed algorithm uses a graph-modeling to develop a scalable and reliable system for gathering and transmitting data. In addition, it extracts the subset of nodes using the artificial intelligence approach and achieves efficient services for the healthcare system. Secondly, symmetric-based digital certificates are utilized to offer authentic and confidential transmission with communication resources using blockchain. The proposed algorithm is explored with existing solutions through multiple simulations and proved improvement in terms of realistic parameters.
The emerging smart city is driving massive transformations of modern cities, facing the huge influx of sensor data from IoT devices. Edge computing distributes computing tasks to the near-edge end, which greatly enhances the service quality of IoT applications, that is, ultralow latency, large capacity, and high throughput. However, due to the constrained resource of IoT devices, currently, systems with a centralized model are vulnerable to attacks, such as DDoS from IoT botnet and central database failure, which can hardly provide high-confidence services. Recently, blockchain with a high security promise is considered to provide new approaches to enhancing the security of IoT systems. However, blockchain and IoT have obvious incompatibility, and low-capacity IoT devices can hardly be incorporated into blockchain with high computing requirements. In this paper, a blockchain-edge computing hybrid system (BEHS) is presented to make the adaptation of blockchain to edge computing and provide trustworthy IoT management services for a smart city. A novel extensible consensus protocol designed for proof-of-work, named proof-of-contribution (PoC), is proposed to regulate the data upload behaviors of nodes, especially the data upload frequency of IoT device nodes, so as to protect the system from attack about frequency. In order to secure the data privacy and authenticity, a data access control scheme is designed by integrating symmetric encryption with asymmetric encryption algorithm. We implemented a concrete BEHS on Ethereum, realized the function of PoC mechanism via smart contracts, and conducted a case study for smart city. The extensive evaluations and analyses show that the proposed PoC mechanism can effectively detect and automatically manage the behavior of nodes, and the time cost of data access control scheme is within an acceptable range.
Jay Mehta, Darsh Mehta, Jainam Jain, Surekha Dholay
Abstractâ The technique of following a product or a batch of things throughout the supply chain to ensure that the products that reach clients are authentic and tamper-proof is known as asset tracking. The ultimate goal of an asset monitoring system is to track products along the supply chain, verifying that they haven't been tampered with and, if they have, pinpointing where the tampering took place. Traditional tracking technologies, such as BLE (Bluetooth Low Energy Beacon), which works within a limited range, RFID, and above-mentioned systems, are expensive and centralised. So, for this project, we'll use Blockchain Technology, which is an immutable, tamper-proof, decentralised distributed ledger with security features that allows us to establish an asset tracker that can follow our product along the supply chain. Ethereum is used to implement the system. Unlike other methods, there are no hardware components or large gadgets that may be removed from the original object and attached to the copy. Keywordsâ Blockchain, Supply Chain, Smart Contract, Keccak-256, Ethereum,GUI
Supply chain applications operate in a multi-stakeholder setting, demanding trust, provenance, and transparency. Blockchain technology provides mechanisms to establish a decentralized infrastructure involving multiple stakeholders. Such mechanisms make the blockchain technology ideal for multi-stakeholder supply chain applications. This chapter introduces the characteristics and requirements of the supply chain and explains how blockchain technology can meet the demands of supply chain applications. In particular, this chapter discusses how data and trust management can be established using blockchain technology. The importance of scalability and interoperability in a blockchain-based supply chain is highlighted to help the stakeholders make an informed decision. The chapter concludes by underscoring the design challenges and open opportunities in the blockchain-based supply chain domain.
Blockchain solutions offer efficient approaches for trustworthy data management, especially in the medical field when storing and processing sensitive patient data. Many institutional and industrial facilities have already recognized the importance of the technology for the health sector and have also formulated basic ideas, concepts and main use cases, but concrete implementations and executions are comparatively rare. This mini review examines current research on specific blockchain implementations in healthcare that go beyond the state of concept studies or theoretical implementation ideas and describes the most promising systems based on systematic literature research. The review shows that secure storage and easy access to complete patient data is becoming increasingly important. Blockchain technology can be used as a secure, transparent and digital way to meet these needs. Hybrid solutions consisting of conventional data storage and blockchain-based access management are increasingly being developed and implemented. The automation of blockchain processes through smart contracts is also recommended. The review further reveals ambiguities in the use of permissioned and permissionless blockchain frameworks, machine learning (ML) integration as well as the question of which data should be stored in the blockchain and how this should be viewed legally. Therefore, there is still a need for further research, especially on these aspects, in order to further establish the use of blockchains in healthcare.
Ovidiu Vermesan, Reiner John, Patrick Pype, G. H. O. Daalderop · 11 authors
The automotive sector digitalization accelerates the technology convergence of perception, computing processing, connectivity, propulsion, and data fusion for electric connected autonomous and shared (ECAS) vehicles. This brings cutting-edge computing paradigms with embedded cognitive capabilities into vehicle domains and data infrastructure to provide holistic intrinsic and extrinsic intelligence for new mobility applications. Digital technologies are a significant enabler in achieving the sustainability goals of the green transformation of the mobility and transportation sectors. Innovation occurs predominantly in ECAS vehiclesâ architecture, operations, intelligent functions, and automotive digital infrastructure. The traditional ownership model is moving toward multimodal and shared mobility services. The ECAS vehicleâs technology allows for the development of virtual automotive functions that run on shared hardware platforms with data unlocking value, and for introducing new, shared computing-based automotive features. Facilitating vehicle automation, vehicle electrification, vehicle-to-everything (V2X) communication is accomplished by the convergence of artificial intelligence (AI), cellular/wireless connectivity, edge computing, the Internet of things (IoT), the Internet of intelligent things (IoIT), digital twins (DTs), virtual/augmented reality (VR/AR) and distributed ledger technologies (DLTs). Vehicles become more intelligent, connected, functioning as edge micro servers on wheels, powered by sensors/actuators, hardware (HW), software (SW) and smart virtual functions that are integrated into the digital infrastructure. Electrification, automation, connectivity, digitalization, decarbonization, decentralization, and standardization are the main drivers that unlock intelligent vehicles' potential for sustainable green mobility applications. ECAS vehicles act as autonomous agents using swarm intelligence to communicate and exchange information, either directly or indirectly, with each other and the infrastructure, accessing independent services such as energy, high-definition maps, routes, infrastructure information, traffic lights, tolls, parking (micropayments), and finding emergent/intelligent solutions. The article gives an overview of the advances in AI technologies and applications to realize intelligent functions and optimize vehicle performance, control, and decision-making for future ECAS vehicles to support the acceleration of deployment in various mobility scenarios. ECAS vehicles, systems, sub-systems, and components are subjected to stringent regulatory frameworks, which set rigorous requirements for autonomous vehicles. An in-depth assessment of existing standards, regulations, and laws, including a thorough gap analysis, is required. Global guidelines must be provided on how to fulfill the requirements. ECAS vehicle technology trustworthiness, including AI-based HW/SW and algorithms, is necessary for developing ECAS systems across the entire automotive ecosystem. The safety and transparency of AI-based technology and the explainability of the purpose, use, benefits, and limitations of AI systems are critical for fulfilling trustworthiness requirements. The article presents ECAS vehiclesâ evolution toward domain controller, zonal vehicle, and federated vehicle/edge/cloud-centric based on distributed intelligence in the vehicle and infrastructure level architectures and the role of AI techniques and methods to implement the different autonomous driving and optimization functions for sustainable green mobility.