An Updated Survey on the Convergence of Distributed Ledger Technology and Artificial Intelligence: Current State, Major Challenges and Future Direction

Bellagarda, Jagger S.; Abu‐Mahfouz, Adnan M.

doi:10.1109/access.2022.3173297

Cited by 20 publications

(7 citation statements)

References 85 publications

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“…Environmental accounting, which measures and reports costs and benefits, is increasingly impacting the FX trading industry (Bellagarda & Abu-Mahfouz, 2022). In the last ten years, stakeholders have been paying rising attention to environmental sustainability issues.…”

Section: Environmental Accounting and Its Relevance To Fx Tradingmentioning

confidence: 99%

“…Some FX trading firms have fully applied AI and blockchain, among other technologies, to their innovations to enable better operations and competition. For instance, JPMorgan Chase has created a trading platform known as DNA, which enables the execution of client orders by comparing client preferences with market data (Bellagarda & Abu-Mahfouz, 2022). In reality, the DNA platform uses machine learning algorithms while analyzing market data and gives signs on when to perform timely trading as needed.…”

Section: Case Studies Of Successful Implementations Of Ai Blockchain ...mentioning

confidence: 99%

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The Future of FX Trading: Exploring the Intersection of AI, Open Innovation, and Industry Evolution

Jones

2024

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The FX trading industry is today witnessing some very strong "winds of change" blowing in from the huge advancements made so quickly in digital technologies, sustainable innovation, and corporate social responsibility. The report will emphasize the evolution of the FX trading industry and its dependence on AI and open innovation. In this case, they reflect the state of the industry at present while offering some critical summaries for future trends that are positioning the industry. This report, therefore, looks at the degree to which banks are resorting to using digital technologies like artificial intelligence, blockchain, and big data analytics to help improve efficiency, transparency, and decisions around trading foreign exchange. This area is more about the trend toward open innovation with AI-based products; developing intelligent systems for big data analysis, pattern finding, or even trading decisions would be possible here. Blockchain technology and smart contracts are potential solutions for ameliorating FX trade transparency, security, and efficiency if implemented. Big data analytics and cloud computing aid in processing and analyzing huge volumes of real-time data. This will also outline how innovation, green initiatives, and sustainable technologies will contribute to and accelerate environmental sustainability. It also advocates for deploying corporate social responsibility and creating trust to grow long-term. Most FX trading firms are responsible for safeguarding the Earth's ecosystem. They invest in renewable energies, efficient technologies for energy, and sustainable infrastructure to lower carbon emissions. There has been a growing stakeholder demand for transparency and accountability in business operations. This phenomenon has enforced progress in accounting for and reporting environmental issues in business. The integration of digital technologies with accounting information systems has transformed the financial operations of FX trading firms. These systems could potentially help businesses automate, How to cite this paper: Jones, K. ( 2024). The Future of FX Trading: Exploring the

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Section: Environmental Accounting and Its Relevance To Fx Tradingmentioning

confidence: 99%

Section: Case Studies Of Successful Implementations Of Ai Blockchain ...mentioning

confidence: 99%

The Future of FX Trading: Exploring the Intersection of AI, Open Innovation, and Industry Evolution

Jones

2024

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“…In the discrete token generation algorithm, a token is generated with the IP address. If a token comprises multiple IP addresses, then it represents a malicious node [33] . The multi-token Proof-of-Stake (PoS) consensus protocol has been suggested for an interoperable system while the validator and nominators act together to improve the security of the system [31] .…”

Section: Problem Assessment: Tokenization and Heter-ogeneous Blockchainsmentioning

confidence: 99%

“…The Polkadot Relay Chain makes the blockchain based system secure and transfers tokens and data. The Parachain [35] network tries to optimize it's all functionality and provides faster transactions at lower costs. The Parachains are customized blockchain that are connected with main blockchain.…”

Section: Problem Assessment: Tokenization and Heter-ogeneous Blockchainsmentioning

confidence: 99%

Token-Based Smart Power Contract for Interoperable Blockchains of Networked Microgrid System

Sharma

2023

New Energy Exploit. Appl.

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Designing the secure and privacy-protected smart power contract between electricity suppliers and consumers, considered agents, of different microgrids, is a challenging task in the networked- microgrid system. A framework is suggested in which each microgrid implements a heterogeneous or isomorphic blockchain based platform. The blockchain interoperability, inherently, is present in different blockchains implemented by various microgrids. This paper reviews the interoperability issues and smart contract designs in blockchain based systems. The paper proposes new mechanisms to cater blockchain interoperability challenges to facilitate the design of secure and seamless smart contracts among different blockchains of microgrids. A network hub of heterogeneous or isomorphic blockchains of network microgrids has been created. A methodology has been developed to transfer tokens between interoperable blockchains. Distributed identity-based microgrid (DIBM) scheme is incorporated to make the networked microgrid system secure and trustworthy. This paper suggests an effective consensus protocol for cross-chain architecture that improves the tokenization system and smart power contract designs. For simulation purposes, MATLAB and python programming have been used with real-time data of microgrids.

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“…Moreover, the black-box problem is addressed through the integration of federated learning (FL) to training machine learning models, each one of them making use of its own dataset, and deep reinforcement learning (deep RL), which combines reinforcement learning (RL) and deep learning techniques. Deep RL is often classified as a narrow AI technique [25]. This groundbreaking approach brings energy efficiency (EE) measures within virtual organizations that dynamically learn from real-time inhabitant data.…”

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confidence: 99%

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort

Márquez-Sánchez,

Calvo-Gallego,

Erbad

et al. 2023

Electronics

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Nowadays, in contemporary building and energy management systems (BEMSs), the predominant approach involves rule-based methodologies, typically employing supervised or unsupervised learning, to deliver energy-saving recommendations to building occupants. However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. This inherent lack of adaptability to occupants significantly hampers the effectiveness of energy-saving solutions. Moreover, the prevalent cloud-based nature of these systems introduces elevated cybersecurity risks and substantial data transmission overheads. In response to these challenges, this article introduces a cutting-edge edge computing architecture grounded in virtual organizations, federated learning, and deep reinforcement learning algorithms, tailored to optimize energy consumption within buildings/homes and facilitate demand response. By integrating energy efficiency measures within virtual organizations, which dynamically learn from real-time inhabitant data while prioritizing comfort, our approach effectively optimizes inhabitant consumption patterns, ushering in a new era of energy efficiency in the built environment.

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An Updated Survey on the Convergence of Distributed Ledger Technology and Artificial Intelligence: Current State, Major Challenges and Future Direction

Cited by 20 publications

References 85 publications

The Future of FX Trading: Exploring the Intersection of AI, Open Innovation, and Industry Evolution

The Future of FX Trading: Exploring the Intersection of AI, Open Innovation, and Industry Evolution

Token-Based Smart Power Contract for Interoperable Blockchains of Networked Microgrid System

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort

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