Elastic Smart Contracts across Multiple Blockchains

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 typically are based on different levels of abstraction and granularity. This poses a number of challenges when multiple blockchains are used together with smart contracts. This paper proposes to apply our concept of elasticity to smart contracts and thereby enabling analytics in and between multiple blockchains in the context of IoTMinisterio de Economía y Competitividad BELI (TIN2015-70560-R)Junta de Andalucia COPAS (P12–TIC-1867)

Blockchain and Distributed Autonomous Community Ecosystems: Opportunities to Democratize Finance and Delivery of Transport, Housing, Urban Greening and Community Infrastructure

This report investigates and develops specifications for using blockchain and distributed organizations to enable decentralized delivery and finance of urban infrastructure. The project explores use cases, including: providing urban greening, street or transit infrastructure; services for street beautification, cleaning and weed or graffiti abatement; potential ways of resource allocation ADU; permitting and land allocation; and homeless housing. It establishes a general process flow for this blockchain architecture, which involves: 1) the creation of blocks (transactions); 2) sending these blocks to nodes (users) on the network for an action (mining) and then validation that that action has taken place; and 3) then adding the block to the blockchain. These processes involve the potential for creating new economic value for cities and neighborhoods through proof-of-work, which can be issued through a token (possibly a graphic non-fungible token), certificate, or possible financial reward. We find that encouraging trading of assets at the local level can enable the creation of value that could be translated into sustainable “mining actions” that could eventually provide the economic backstop and basis for new local investment mechanisms or currencies (e.g., local cryptocurrency). These processes also provide an innovative local, distributed funding mechanism for transportation, housing and other civic infrastructure

IoT Ecosystems Enable Smart Communication Solutions: A Case Study

The Internet of Things (IoT) is a platform for innovation, allowing people to invest in and use IoT to improve life, business, and society. It will be applicable to all or any industry sectors, verticals, people, machines, and everything. This creates difficult requirements in terms of higher system capacity, extremely low latency, such as for the tactile Internet, extremely high throughput values, a wide range of services, such as IoT and M2M, and a more uninterrupted experience. As a symbiotic confluence of up to date and existing technologies, the IOT architecture will use Hetnet RAN, Cloud enhanced RAN, and SW defined data centres to combine novel and legacy technologies. As a result, IOT will combine next-generation largearea extensible service experiences anytime and anywhere, with ultra-dense installations, nearzero latency, and GB experiences–when and where it matters. Collaboration on research, standardisation, and spectrum sharing with the IT/Internet world, industry verticals, policymakers, and academia is a significant success element. Trillions of dollars in smart ecosystems prospects covering secure connections, digital service enablement, applications and repair provisioning, and a wide range of internet of things and consumer applications are available to communications service providers and enterprises

Designing Data Spaces

This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty

The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0

Industry 4.0 is expected to impart profound changes to the configuration of manufacturing companies with regards to what their value proposition will be and how their production network, supplier base and customer interfaces will develop. The literature on the topic is still fragmented; the features of the emerging paradigm appear to be a contested territory among different academic disciplines. This study assumes a value chain perspective to analyze the evolutionary trajectories of manufacturing companies. We developed a Delphi-based scenario analysis involving 76 experts from academia and practice. The results highlight the most common expectations as well as controversial issues in terms of emerging business models, size, barriers to entry, vertical integration, rent distribution, and geographical location of activities. Eight scenarios provide a concise outlook on the range of possible futures. These scenarios are based on four main drivers which stem from the experts\u2019 comments: demand characteristics, transparency of data among value chain participants, maturity of additive manufacturing and advanced robotics, and penetration of smart products. Researchers can derive from our study a series of hypotheses and opportunities for future research on Industry 4.0. Managers and policymakers can leverage the scenarios in long-term strategic planning

An Improve the Onboarding Process in Trade Finance Applications Using Blockchain Technology

Today, challenges in Know Your Customer (KYC) and Anti-Money Laundering (AML) processes include inefficiencies, data silos, and the risk of fraudulent activities. Integrating blockchain technology offers a transformative solution to these issues. Blockchain's decentralized and tamper-resistant nature ensures a single, verifiable source of truth for customer information, reducing data discrepancies across institutions. Smart contracts can automate AML compliance checks, ensuring real-time monitoring and rapid response to suspicious activities. The immutability of blockchain records enhances auditability, facilitating regulatory compliance. Furthermore, the secure and transparent nature of blockchain instills trust among stakeholders, fostering collaboration in combating financial crimes. By leveraging blockchain in KYC and AML processes, the financial industry can achieve enhanced efficiency, reduced fraud, and strengthened regulatory adherence

Elastic Smart Contracts in Blockchains

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.Ministerio de Ciencia, Innovación y Universidades RTI2018-101204-B-C21 (HORATIO)Junta de Andalucía APOLO (US-1264651)Junta de Andalucía EKIPMENT-PLUS (P18-FR-2895

Artificial intelligence potential for net zero sustainability: Current evidence and prospects

oai:repository.uel.ac.uk:8xqzxThis comprehensive review explores the nexus between AI and the pursuit of net-zero emissions, highlighting the potential of AI in driving sustainable development and combating climate change. The paper examines various threads within this field, including AI applications for net zero, AI-driven solutions and innovations, challenges and ethical considerations, opportunities for collaboration and partnerships, capacity building and education, policy and regulatory support, investment and funding, as well as scalability and replicability of AI solutions. Key findings emphasize the enabling role of AI in optimizing energy systems, enhancing climate modelling and prediction, improving sustainability in various sectors such as transportation, agriculture, and waste management, and enabling effective emissions monitoring and tracking. The review also highlights challenges related to data availability, quality, privacy, energy consumption, bias, fairness, human-AI collaboration, and governance. Opportunities for collaboration, capacity building, policy support, investment, and scalability are identified as key drivers for future research and implementation. Ultimately, this review underscores the transformative potential of AI in achieving a sustainable, net-zero future and provides insights for policymakers, researchers, and practitioners engaged in climate change mitigation and adaptation

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business