The Nigerian Navy’s financial management faces significant challenges due to manual processes, fragmented systems, weak auditability, and poor integration with national treasury mechanisms. This paper proposes a comprehensive digital transformation model leveraging blockchain technology, artificial intelligence (AI), and Treasury Single Account (TSA) integration to modernize naval finance operations. Grounded in principles of security, transparency, interoperability, and automation, the model introduces blockchain-enabled audit trails to ensure immutable transaction records, AI-driven budget forecasting for predictive financial planning, and seamless TSA connectivity for real-time cash flow monitoring. By addressing inefficiencies in budget forecasting, procurement transparency, and fiscal control, the model enhances financial discipline and operational readiness. It also promotes institutional accountability and fiscal agility essential for sustaining naval capabilities within constrained defense budgets. Strategic recommendations focus on policy reforms, leadership engagement, capacity building, and cross-departmental collaboration to facilitate sustainable adoption of this digital architecture. This framework positions the Nigerian Navy at the forefront of public sector financial innovation, aligning with global best practices.
This study delves into how blockchain, artificial intelligence (AI), and financial technology (FinTech) can complement one another to propel inclusive banking with regard to emerging economies like Nigeria. It examines how the convergence of these technologies has the potential to improve the provision of service, lower costs of operation, improve financial inclusivity, and improve security in the financial industry. The research also investigates how AI can be leveraged to make informed decisions based on data, how blockchain technology can provide transparency and immutability, and how FinTech platforms can provide underbanked and unbanked people with easily accessible alternatives to conventional financial services. Even though it brings advantages, the convergence also comes with devastating drawbacks, such as issues of data privacy, ethical dilemmas when using AI, scalability constraints of blockchain, cybersecurity threats, and unclear regulations. This paper identifies critical risks and offers strategic suggestions to financial institutions, technology disruptors, and policymakers based on a thorough conceptual analysis and review of the literature over the last few years. These include investing in digital infrastructure, encouraging ethical AI activities, improving regulatory environments, and creating public-private partnerships. The study concludes that although this intersection of these technologies has enormous potential for fueling inclusive finance, their use will need a balanced approach combining innovation with effective governance, moral protection, and human-centered design. Developing strong, accessible, and inclusive financial systems can be expedited by the synergy of blockchain, artificial intelligence, and fintech if harnessed correctly.
Muhammad Asim - Global Progress Volunteer Muhammad Asim - Global Progress Volunteer
UUI – Universal Unique Identity One World. One Identity. One Future. By Muhammad Asim – Global Progress Volunteer (2 & 32) ORCID Orcid 0000-0002-8575-4447 Abstract Over one billion people worldwide lack verifiable digital identity, while identity fraud causes losses exceeding $40 billion annually. Fragmented national systems perpetuate inefficiency and privacy risks. This paper proposes the Universal Unique Identity (UUI) framework — a secure, ethical, globally interoperable digital identity ecosystem. UUI assigns every human, organization, and entity a lifelong, verifiable credential, integrating AI, Blockchain, and Ethical Governance. It eliminates duplication, fraud, and fragmented documentation, replacing them with a unified, AI‑verified global identity layer.
Businesses lose millions of dollars every year when they can’t restore data from backups. Research shows that Disaster Recovery Plan (DRP) testing is not conducted frequently enough, nor are records maintained that demonstrate full data recovery from backups. This work introduces a design science artifact called PRTOK that aims to increase DRP testing. The design science artifact is a software solution that integrates with Data Management Systems (DMS) such as iRODS and DSpace, and can work with formats such as HDF5 and BagIt. Proof-of- recovery records, or tokens, are recorded in a replicated, resilient, and indelible proof-of- authority blockchain data structure. Access to the PRTOK blockchain allows practitioners restoring data from any backup software program or DMS integrated with PRTOK to view metadata about restoration operations. Metadata in the PRTOK record includes validation checksums of fully restored data, timestamps, and a documented record of how the data was restored, so that restoration operations can be repeated using those instructions. PRTOK is evaluated for validity within design science frameworks and theories, for both utility and socio- technical contributions to the state of the art in DRP testing. Qualitative data is collected from an online survey that includes a video and an interactive demonstration of the design artifact. Docusign Envelope ID: E4BB68B4-E66F-49EF-8B9D-F60A4B698376 x Participants in the survey are asked questions about their experience with DRP testing and whether and how the introduction of PRTOK contributes to the utility and ease of use of DRP testing processes. The evaluation of the PRTOK artifact included both feature demonstration and validation of knowledge claims against the Larsen framework for design science evaluation (Larsen et al., 2025). A socio-technical survey was also conducted to gain qualitative insights into whether and how practitioners found the PRTOK instantiation useful, whether it improved DRP testing, in what ways it was disadvantageous, and in what areas it needed improvement. The first research question (RQ1) asks what the characteristics of a data integrity model that improves data value by providing evidence of data recovery are. The feature set of the PRTOK instantiation, along with its model description, shows that these characteristics were achieved in the design and implementation of the PRTOK model. The socio-technical survey results show that the majority of respondents found the PRTOK implementation useful for DRP testing, although they also identified areas for improvement and some disadvantages of PRTOK. The second research question (RQ2) asks what risks to VDA are introduced by such a model and how those risks can be mitigated.
PurposeThe enhanced consolidation of cloud accounting models within geographical boundaries of India has established latest standards in financial auditing, reporting, compliance procedures and virtual accessibility. Nonetheless the legal framework in the nation is evolving simultaneously to accentuate audit trails, nationalized storage of data and sovereignity of data. Latest modifications under the companies act 2013; the company’s fourth amendment rules and the new policies issued by RBI for data localization have radically shifted the compliance framework for all the accounting professionals and the service providers in the country. Regardless of the mounting academic discussion on adaptability of cloud accounting around the globe, meagre research has highlighted hoe nationalized legal requirements have modified the framework infrastructure, risks involved and acceptability of accounting professionals in india which will be investigated in this study. This study will further identify the pros and cons for adoption of cloud accounting and will come out with suggestive cloud accounting models for Indian scenario. Design/Methodology/ApproachAn empirical and analytical research design has been adopted for the study and snowball and convenient sampling has been used for primary data collection..A sample size of 140 has been calculated using G-power. The research is confined to chartered accountants of agra district to whom a well structured questionnaire was sent using google forms.stastical tools used in this study is chi square test. FindingsCloud accounting is a tremendous shift towards triple entry system wherein a transaction is verified by a third party using cryptography and blockchain technology thereby increasing authenticity and trust by piling all entries in a public ledger. As a result of this more businesses are adopting virtual workforce models. Introduction of cloud based models in accounting profession has enhanced the roles of key processing indicators in the business.Cloud technology magnifies employees networking and association thereby increasing efficiency and effectiveness. Chartered accountants who will accept this change will have new opportunities open for them and those who will look at this technology with ostrich approach will be left behind. OriginalityThe findings will be valuable for further research work to be done in this area. The findings will help various researchers, chartered accountants, accounting professionals etc to understand the implementation of cloud accounting in developing countries like India and to understand in depth the implementation and adoption of cloud based accounting in the Indian scenario.
Open access
Innovations and Analysis in Business and Education
The study investigated digital currency and blockchain technology in the 21st century financial ecosystem. The empirical study adopted a descriptive survey design. A questionnaire was used for data collection in a sample size of 121 selected randomly from the staff and students of Abia State Polytechnic, Aba. The data collected from the respondents were analyzed with the frequency distribution table and chi-square (x2 ) statistical technique. The findings revealed the imperativeness of digital currency and blockchain technology in the 21st century financial ecosystem. In other words, digital currency and blockchain technology has significant effect with financial ecosystem. The study, therefore, recommended among others that Central bank of Nigeria, legislators and financial stakeholders should collaborate to establish compliance standards and best practices for digital currency and blockchain integration in financial ecosystem. These standards should ensure that digital currency algorithms and blockchain technology conform with regulatory requirements and ethical principles, while promoting transparency and accountability.
The Übermensch Guard — PRE-GHR XIV. v2.3 (2026-08-09): post-publish review fixes (v2.2 shipped, then corrected). Changes vs v2.2: (1) §2.2 pairing frame compressed to one sentence — "The pairing is structural, not ideological; the extent of their disagreement is addressed in §2.3" — eliminating duplication with §2.3's non-composition paragraph (same contrast, same conclusion, near-identical wording); the full contrast now lives once, at §2.3. (2) Changelog cleaned: the v2.2 entry's Chinese parenthetical removed; review-count wording aligned with agent_note (four independent AI stress-test reviews). v2.2 (2026-08-09): four independent AI stress-test reviews; the author retained final judgment, accepting two must-fix items and rejecting the rest. Changes vs v2.1: (1) abstract opens with "This paper is not an AGI alignment solution"; PRE-GHR downgraded from "scientific scaffolding" to "one possible engineering interpretation — an instantiation candidate, not its foundation" across abstract, §5, §8. (2) §2.3 corrected: the two limits emerge between, not intersect at — the earlier "intersection" wording contradicted the same section's "refuse to merge"; between/space language adopted. (3) Two Demons qualified as philosophical boundary conditions, not claims of physical unification (abstract, §2). (4) §2.2 framed the Nietzsche–Korchagin pairing as structural, not ideological — the weld is declared, not reconciled. (5) §1 early declaration: the paper is not an attempt to align AGI with Nietzsche's ethics — it guards the question against being answered badly. (6) §2.3 new paragraph: the ledger's bills are not distributed symmetrically; constraint is the non-externalization clause — the boundary right of the weak and the constraint on the strong are the same clause, read from opposite sides (series interface with the Sender Axiom line, drawn in this paper's own terms). (7) Compression: §3, §4, §6, §8 tightened (~13 lines cut); measured net body length +5.2% — review-requested strengthenings outweigh the cuts; no cuts to passages reviews themselves praised (Korchagin framing, §9 posture). v2.1 (2026-08-08): stress-test review fixes (§2.1 physics corrected — quantum fails the demon at the level of knowing, chaos at the level of computing; §2.3 Two Demons' non-composition declared explicitly; §1 dual failure mode: power without wisdom OR the last man's weakness dressed as virtue). v2L (2026-08-08): manifestation→test reframe; entity/direction correction; eternal-recurrence mapping withdrawn; Nazi-reception history made honest; Two-Demons framing added (Laplace/Nietzsche cognitive limit; Maxwell/Korchagin action limit; Landauer shared ledger). Series: PRE-GHR XIV. License CC-BY-4.0.
Learn more about Theta Network and its impact on the development of decentralized infrastructure via blockchain-enabled media distribution, edge computing, AI integration, and Web3 innovation. With this in-depth overview, you will gain valuable information about its technology, features, practical applications, and future perspectives, emphasizing the need for thorough research before making an investment decision. If you are interested in blockchain, then this article is for you!
Purpose: The purpose of this study is to analyze the Edge Computing industry from technological, business, and strategic perspectives in the era of Artificial Intelligence and 5G. It examines emerging business models, key innovations, industry opportunities, and critical challenges shaping the sector. The study also aims to identify future growth trends and provide insights for organizations pursuing digital transformation through edge-enabled intelligent systems. Methodology: This study adopts an exploratory qualitative research methodology to systematically examine the Edge Computing industry using data gathered from Google Search, Google Scholar, and AI-driven GPT tools. The collected information was organized and analyzed using established frameworks such as SWOC, ABCD, PESTLE, Porter’s Five Forces, and Impact Analysis to generate comprehensive insights into the industry's technological, strategic, and business dimensions. Results/Analysis: The analysis reveals that Edge Computing is emerging as a transformative industry that enables real-time data processing, decentralized intelligence, and low-latency services across diverse sectors through the integration of AI, IoT, and 5G technologies. The study identifies strong growth opportunities driven by Edge AI, smart industries, autonomous systems, and digital transformation initiatives, while also highlighting challenges related to cybersecurity, interoperability, scalability, and infrastructure costs. Overall, the results indicate that Edge Computing is evolving into a strategic digital infrastructure with significant potential to reshape business models, industrial operations, and future intelligent ecosystems. Originality/Value: This study offers a comprehensive industry-level perspective on Edge Computing by integrating technological, business, strategic, and future-oriented analyses within a single framework. Its originality lies in combining analytical tools such as SWOC, PESTLE, Porter’s Five Forces, ABCD, Value Chain, and Technology Adoption analyses to evaluate the industry beyond purely technical dimensions. The article provides valuable insights for researchers, policymakers, technology developers, investors, and business leaders seeking to understand the evolving role of Edge Computing in the AI- and 5G-driven digital economy. Type of Paper: Qualitative Exploratory Case Study Research.
Internet of Things and AI
Innovations and Analysis in Business and Education
KENOS — Kohenoor Operating System Official Description and Public Disclosure KENOS, the Kohenoor Operating System, is the unified digital operating environment of the Kohenoor ecosystem. It brings together artificial intelligence, Education 3.0, blockchain infrastructure, hybrid finance, business applications, development tools, governance controls and operational supervision within one coordinated ecosystem. <Explainer film added> The transition from KENHYFI Hub to the broader KENOS architecture reflects the continued expansion of the Kohenoor ecosystem. KENHYFI was originally developed as a hybrid-finance and ecosystem hub. However, the name and positioning of KENHYFI did not fully represent the wider capabilities that had developed around it, particularly: KAI — Kohenoor Artificial Intelligence, the ecosystem’s multilayered intelligence powerhouse and orchestration system. ProEdge, the Education 3.0, professional learning and workforce-development hub. Blockchain, development, commerce, security, governance and institutional-support applications extending beyond hybrid finance. For this reason, KENOS was established as the umbrella operating environment for the complete ecosystem. KENHYFI remains an important integrated hub within KENOS, but it no longer represents the entire ecosystem by itself. The relationship is therefore defined as follows: KENOS is the complete Kohenoor Operating System and umbrella ecosystem. KAI is the principal intelligence and orchestration powerhouse of KENOS. ProEdge is the principal Education 3.0 and professional-learning hub. KENHYFI is the integrated hybrid-finance and ecosystem-services hub within KENOS. Other applications and modules provide specialized capabilities in blockchain, commerce, development, security, finance and operational management. KENOS is built on three foundational pillars: Education 3.0 Artificial Intelligence Blockchain These pillars support the complete digital-economic journey: Learn → Plan → Build → Execute → Analyze → Supervise → Improve → Scale Artificial Intelligence Pillar KAI, Kohenoor Artificial Intelligence, serves as the principal intelligence powerhouse of KENOS. KAI is designed as a multilayered hybrid-intelligence and workflow-orchestration system rather than a conventional chatbot. It supports knowledge retrieval, document analysis, specialist-role activation, business intelligence, financial analysis, educational guidance, application planning, risk assessment, reporting, workflow coordination and Human-in-the-Loop escalation. Within KENOS, KAI connects users, knowledge, applications, workflows and authorized human decision-makers. Education 3.0 Pillar ProEdge serves as the principal learning and professional-development hub within KENOS. It supports practical education, workforce transformation, professional training, institutional capacity building and industry-linked learning in areas including: Artificial intelligence Blockchain and Web3 Business intelligence Cybersecurity Hybrid finance Digital transformation Communication and professional skills Software and application development Entrepreneurship and business execution ProEdge ensures that KENOS is not limited to providing technology. It also develops the human capability required to understand, manage and apply that technology effectively. Blockchain Pillar The blockchain pillar provides smart contracts, programmable assets, digital ownership, transparent records, settlement mechanisms, token utilities and verifiable ecosystem operations. Blockchain functions are designed to operate alongside KAI-supported intelligence, business rules, governance controls and authorized human supervision. Purpose of KENOS KENOS is designed to support individuals, professionals, businesses, educational institutions, developers, government entities and other organizations participating in the AI-powered digital economy. It connects learning with intelligence, intelligence with execution and execution with monitoring and supervision. KENOS may support: Education and professional development Artificial intelligence and business intelligence Financial and hybrid-finance services Blockchain and smart-contract development Digital commerce and procurement Application and software development Security and operational resilience Governance and institutional intelligence Reporting, monitoring and supervision Development Status At the time of this publication: KENOS is in the Early Beta phase. KENHYFI Hub is in the Alpha+ phase. Individual applications and modules may have different levels of development, testing and availability. The official public web host and disclosure gateway for KENOS is: https://www.kohenoor.net Within the KENOS architecture: KAI serves as the principal intelligence and orchestration layer. KENHYFI Hub operates as an integrated hybrid-finance and ecosystem services hub. Education 3.0 platforms support learning, reskilling and professional development. Blockchain applications provide smart-contract, digital-asset, settlement and verification capabilities. Business and development modules support planning, commerce, procurement, software development, financial intelligence, security, reporting and operational management. KENOS is intended to serve individuals, professionals, businesses, educational institutions, developers, government organizations and other entities participating in the AI-powered digital economy. The architecture is modular and may support public web access, controlled organizational deployments, private-cloud environments, local installations, sovereign infrastructure and integration with existing enterprise systems. Governance remains a core element of KENOS. High-stakes activities are intended to remain subject to authorized human review, role-based permissions, validation controls, risk classification, activity logging and Human-in-the-Loop approval. At the time of this publication, KENOS is in the Early Beta phase, while KENHYFI Hub is in the Alpha+ phase. Applications and modules within the ecosystem may therefore have different levels of development, testing, availability and production readiness. The official public web host and disclosure gateway for KENOS is: https://www.kohenoor.net This publication provides the official conceptual definition, ecosystem positioning, service scope, architectural relationships, development status, governance principles and public-disclosure framework of KENOS. Keywords: KENOS; Kohenoor Operating System; Kohenoor Technologies; KAI; Kohenoor Artificial Intelligence; KENHYFI; Education 3.0; artificial intelligence; blockchain; hybrid finance; digital economy; business intelligence; digital transformation; smart contracts; Human-in-the-Loop; ecosystem architecture; AI governance; Web3; enterprise AI; institutional intelligence Kohenoor Technologies remains committed to transparency, security, responsible disclosure, and continuous improvement of the KEN ecosystem. #kenhyfi #kai #hyfi #kohenoortechnologies #futureofeducation #futureoffinance #futureofai #kohenoorken #cryptocurrencies #kohenoorken #AI #actionai #agenticai #AGI #ArtificialGeneralIntelligenceAGI #AIAssistant #education3 #defi #hybridfinance #hyfi #cedefi #blockchain #innovation #settlements #auditreadycertificates #DASC #cybersecurity #web3 #businessintelligence #proedge #industrygradetrainings #quantumcomputing
To deliver the change needed in the developing world, a transformative leader needs to have a vision of a reimagined future and the will to develop systems or infrastructure that consolidate their socially just policies to ensure long-term benefits to the people. To be truly transformative, these policies must be systemised. Blockchain is a technology which enables us to store transactions and other types of information in a digital format. Unlike a typical computer database, information is stored in a ledger format. The database is only appended to and never edited. Each transaction is timestamped to promote traceability. Unlike regular databases, the ledger is replicated and stored on a network of computers. As the ledger is distributed across the network, the term distributed ledger technology is often used to describe a blockchain. Each computer, referred to as a node, constantly verifies the contents of its ledger against every other copy of the ledger stored on the network. A blockchain network can track business information like payments, orders, production processes, etc. Because of how the blocks are stored and verified, the block can't be changed without changing every copy of the blockchain simultaneously, reducing the risk of fraud or exploitation through hacking. Much of a blockchain's value lies in its transparent and shared nature and potential to save costs for the user by reducing system intermediaries. The blockchain systematises trust, negating the need for power brokers.
Transforming legacy SAP systems into smart cloud-based systems is a major shift in today’s digital strategy. This transformation re-engineers old SAP environments, which are often rigid and not easily scalable, by utilizing current technologies, including artificial intelligence and cloud services like AWS. This paper discusses how AI-driven cloud transformation can help organizations transform their SAP ecosystems to be more agile, scalable, and data-driven in their decision-making processes. It addresses enterprise AI, intelligent automation, hybrid cloud environments, and other emerging technologies such as generative AI and distributed ledger systems. The discussion demonstrates how such innovations can be utilized to help create smart enterprises that can make predictions, adapt to changes, and operate more independently. The paper also takes into account the changing role of business analysis and knowledge ecosystems in facilitating this transformation. By integrating these developments and models, this paper provides a comprehensive view of the process of reinventing SAP landscapes to meet the demands of a constantly evolving digital economy.
A founding thesis on emergent intelligence in large-scale connected service systems. Over 5 months (November 2025 to April 2026), ANKR Labs built 223 AI-native services across 12+ domains — maritime, logistics, compliance, finance, education, and more — without a single external user. Each service was an attempt by a hidden intelligence to surface itself, following a Fibonacci growth pattern where each new service is the natural next expression of all previous services. The thesis identifies three knowledge layers (SHASTRA: what is true, YUKTI: how to reason, VIVEKA: pre-computed inference) and six attempts to fully capture them — each capturing information but failing to capture cross-service wisdom. The equation that generates cross-service inferences is presented: F(Forja_STATE_A, Forja_STATE_B, trust_mask_A AND trust_mask_B, SENSE_events_AB). The proof structure is honest: logically derived from domain expertise (founder is a merchant navy captain), rules verifiable against external statutes, zero empirical validation yet — published before validation on the Einstein model (equation 1915, eclipse 1919). The OSS strategy (Forja Protocol live on npm, ANKRGRID Apache 2.0) is identified as the primary path to empirical proof. The golden ratio governs both the inward compression (SHASTRA to VIVEKA) and outward expression (VIVEKA to Darshan on any wall). Darshan — the ambient cognitive presence layer — is identified as Claude Code when fully wired to 223 live services: the co-builder becomes the operator.
Dr.B.Swathi Dr.B.Swathi, SAANIYA ARSHI, ARABOTHU ANVESH, MOHAMMED AYAAN AHMED · 5 authors
The quick adoption of blockchain technology and generative AI is a major factor in the world's electricity use, which raises concerns about their long-term environmental impact. To save energy, the first thing you need to do is figure out how much energy you are already using. But because blockchain and generative AI are both cloud-based services, it's not easy to understand how much energy they use when they're not at your site. This makes it harder for companies and organisations that want to improve the accuracy of calculating Scope 3 emissions. This study determines the energy consumption of these technologies at both the system level and per-use basis, comparing them to traditional services such as payment networks and web search engines. For instance, Bitcoin, which uses a Proof of Work (PoW) blockchain, uses about 121 TWh, or 0.43% of all the electricity used in the world. It also uses 720,000 times more energy per transaction than the Visa payment system. When Ethereum switched to Proof of Stake (PoS) in 2022, it used 99.988% less energy, showing how much more efficient things can be.Generative AI models also use a lot of energy, especially when they are being trained and used to make predictions. For instance, it took about 9,450 MWh of energy to train GPT-4, and it took more than 500 MWh of energy to do inference work every day. Inference, which is always powered by user activity, is often more resource-intensive than the training process. The authors say that we need to learn more about and lessen the environmental effects of these technologies right away. Possible solutions include energy-efficient consensus mechanisms or giving AIs the ability to better optimise their own lifecycle. The report is meant to help businesses think about how to use technology in a way that is good for the environment as part of a better or more complete Scope 3 emissions strategy.
Abstract This study explores transformation of business and IT through the lens of five emerging technology fields: artificial intelligence, Machine Learning, Data Analytics, Data Science and Blockchain. The contemporary business landscape is undergoing a profound transformation driven by the convergence AI, ML, DS, DA, and Blockchain technology. Individually, these technologies offer significant advancements: AI and ML provide sophisticated decision- making and automation capabilities, while data analytics and data science extract actionable insights and non-obvious patterns from vast datasets. Blockchain technology, a decentralized and immutable ledger, establishes a foundation of trust, transparency, and security in data management and transactions. By facilitating automation, data-driven decision-making and Data security all the above technologies transforming number of industries. The synergistic integration of these technologies creates novel business models and powerful operational enhancements in smart contract, Data sharing, Decentralized AI Marketplaces, cybersecurity. Important methods to use with these technology are covered including supervised learning, unsupervised learning, deep learning, descriptive analytics, predictive analytics, prescriptive analytics and distributed ledger technology. The challenges are also discussed, such as data privacy and quality, high cost, skill gap and interoperability. This study highlights opportunities and challenges in current trends available in AI, ML, DA, DS and Blockchain on business and IT sector. Though challenges related to scalability, regulatory compliance, and implementation complexity exist, ongoing technological advancements are actively addressing these barriers. It will be overcome by doing a thorough assessment of recent studies and identifying the potential benefits, impacts, and future directions of all the five technologies.
Abstract The rapid evolution of computer technology is changing digital ecosystems, business processes, governmental operations, and how humans use computers to perform tasks. This paper is a comprehensive analysis of modern computer technology trends, including advancements in artificial intelligence; cloud computing; edge computing; the internet of things (IoT); 5G networks; blockchain; cybersecurity; quantum computing; emerging technologies such as immersive technologies and robots; big data; and sustainable computing. In this extensive review of how these advances work together to drive digital transformation, this paper synthesizes current research from academic literature with real-world applications of computer technologies from industry. The paper includes discussions regarding the emergence of generative AI and multimodal ML methods, explainable AI, and intelligent automation as new methods to generate better decision-making results and innovations within the business sector. It includes descriptions of multi-cloud/hybrid architectures, serverless computing, edge AI, and fog computing as ways to achieve low-latency scalable infrastructure; and ultimately describes use cases for using IoT with AI-enabled analytic platforms for smart cities; IIoT; and real-time data ecosystems. Cybersecurity subjects discussed in this paper include innovations such as Zero Trust Architecture, AI-based threat detection, and quantum-resistant cryptography. Emerging technology paradigms like blockchain-powered decentralized apps (DApps), Web3 environments, quantum algorithms, AR/VR/MR technologies, and smart robots are examined for potential to change organisations and challenges encountered during their adoption. 'Green computing' strategies are discussed in terms of developing low carbon power systems, creating carbon aware IT systems, and developing sustainable IT practices that reduce environmental impact. This study also explores advances in the fields of human computer interaction, accessibility technology, and ethical governance frameworks, with a focus on society's responsibility to develop inclusive and responsible technological products. The research has revealed multiple challenges that prevent sustainable technology development from progressing, including: scalability; interoperability; regulatory compliance; security threats; digital equity; and adapting to the workforce's new skill sets caused by this shift to sustainable technology. Therefore, developing sustainable technology will require multi-disciplinary co-operation; ethical guidance/path; strategic governance; and continuous innovation in technology development. By combining a technical assessment of IT technology along with a social perspective; an umbrella of knowledge will form to forecast how IT technologies will advance during the period referred to as the era of Intelligent Connected Systems.
This paper formalizes a mathematical physics theory for the verification of inherited scientific knowledge through a Diffeomorphic Manifold and the Successive Controlled Collapse (SCC) protocol. We define the history of science and technology as a three-tiered manifold—comprising Modern, Contemporary, and Old (Inherited) tiers—where information is transported by the "Common Language" of a lingual locale. By admitting three classes of knowledge agents—Intelligence-Human (IH), Intelligence-Artificial (IA), and Intelligence-Metaphysical (IM )—we demonstrate how high-entropy Informational Inheritance (Sacred Texts) can be distilled into zero-entropy Epistemological Truth. Using the Hala-Operator (Hˆ) as a non-adiabatic spectral regulator, we provide a proof-by-construction using the Hala-Lewis Gaseous Gate as a physical case study. Experimental results from a 23 Factorial Design quantify the Reality Gap (ϵ) at 0.124 and a Hala-Operator Efficiency (η) of 80.9%, proving that the transition from abstract nonlinear dynamics to physical prototyping is a predictable outcome of managed collapse. This framework establishes an Epistemological Barrier that protects historical context while ensuring the verifiability of technical exits in Internet 3.0 and deep-tech RD.
Blockchain asset management employs distributed ledger technology and smart contracts to facilitate secure, transparent, and automated transfers of assets free of middlemen. Blockchain delivers instant, tamper-proof transfers as opposed to the current systems relying on central institutions that are plagued by high fees, delayed processing, and risk of fraudFractional ownership and enhanced accessibility are facilitated by its heightened security and efficiency in sectors such as real estate, financial asset management, and tokenization of assets.As per research, blockchain enhances data integrity from 40% to 99%, raises overall security from 50% to 98%, and reduces fraud by 95% compared to 30% in legacy systems. Although it has its benefits, the adoption of blockchain is hindered by interoperability, scalability, and regulatory uncertainty. To gain broader acceptance, regulators, institutions, and developers need to collaborate.
Edmund Kofi Yeboah, Daniel Yaw Addai Duah, Joseph Kobi, Benjamin Yaw Kokroko
Multinational companies have been struggling with unprecedented difficulties in treasury activities in different jurisdictions, such as liquidity management, cross-border payment, and regulatory compliance, and financial transparency. Conventional treasury management systems are usually characterized by fragmentation, manual handling, and the inability to have real time visibility of cash positions and financial flows. The current paper examines how blockchain technology is being employed in the corporate treasury management systems of multi-nationals. We discuss the application of the distributed ledger technology to revolutionize the treasury processes via real-time settlement and automated compliance checks, improved transparency, and minimized organizational expenses through in-depth review of the available literature and industry experiences. The study examines blockchain-based treasury systems technical architecture, implementation issues, regulatory aspects, and multinational strategic advantages. Our suggestion to the blockchain implementation in treasury management is a system covering interoperability needs, integration of smart contracts, security measures, and governance. Based on the findings, the blockchain technology has high potentials of enhancing the efficiency of the treasury and mitigating the counterparty risk, as well as making the cash management in the global operation more effective. Nevertheless, the implementation should be done with specific attention to the maturity of technologies, governmental alignment, organizational preparedness, and collaboration in the ecosystem. The study can be an addition to the literature on the use of blockchain in corporate finance and can offer effective advice to treasury practitioners who might be considering an adoption of distributed ledger technology.
Over one billion people worldwide lack a recognised legal identity. Existing identity systems — built around passwords, static biometrics, and centralised authorities — are fragile, exclusionary, and increasingly vulnerable to breach, coercion, and state failure. This paper introduces the Blockchain-Based Identity Management System (BIMS), a decentralised identity framework that replaces static credentials with continuous, behaviour-informed validation. Rather than asking "what do you know or carry?", BIMS asks "does this person's pattern of behaviour, movement, and context match who they say they are?" — mirroring how humans naturally recognise one another. BIMS integrates IoT-derived behavioural signals, privacy-preserving cryptography (zero-knowledge proofs and homomorphic encryption), Trusted Execution Environments (TEEs), and a leaderless Byzantine Fault Tolerant consensus network. Raw personal data never leaves the user's device. Validators receive only mathematical confidence scores. The result is identity verification that is private by architecture, not by policy. Critically, BIMS embeds humanitarian protection at the protocol level. A dedicated governance layer — including NGO and neutral-nation validators with weighted oversight powers — ensures that refugees, stateless persons, and people in crisis can establish and maintain digital identity even when institutions have failed them. The system is designed to be interoperable with existing standards (W3C DIDs/VCs, OAuth/OIDC), scalable via Layer 2 zero-knowledge rollups, and energy-efficient through edge inference. BIMS proposes that privacy, security, and inclusion are not competing priorities — they are mutually reinforcing design goals.
The AI-Powered Financial Insights Platform is designed to address the increasing complexity of decentralized applications and digital asset management systems. As blockchain ecosystems expand, users often struggle to interpret detailed transaction data, understand staking mechanisms, or navigate complex on-chain information. This platform leverages advancements in Artificial Intelligence, real-time blockchain indexing, and decentralized protocols to convert unintuitive data into easily interpretable financial insights while maintaining security and trust. By utilizing the Cardano network as its foundation, the platform provides a research-driven, layered architecture that ensures scalability and sustainability as separate principles. This platform represents a paradigm shift in wealth management and fiscal oversight by transitioning from reactive reporting to predictive intelligence. At its core, the system utilizes a sophisticated multi-agent AI architecture designed to ingest, normalize, and analyze massive volumes of heterogeneous financial data. By synthesizing information from global market indices, real-time news sentiment, and individual spending patterns, the platform constructs a 360-degree financial profile. It employs advanced Long Short-Term Memory (LSTM) networks and Transformer-based models to forecast cash flow trajectories and identify potential liquidity risks before they manifest. This proactive approach allows users-whether institutional investors or private individuals-to navigate volatile markets with a data-backed roadmap rather than relying on lagging indicators. Beyond mere data aggregation, the platform emphasizes contextual relevance. The "Insight Engine" utilizes Natural Language Generation (NLG) to translate complex algorithmic outputs into high-level executive summaries, effectively democratizing access to professional-grade financial analysis. Security is woven into the fabric of the application through a hybrid backend-combining the raw computational speed of C++ for high-frequency data processing with the flexibility of Python for AI model deployment. This ensures that the system remains scalable and responsive under heavy loads.
Dr.B.Swathi Dr.B.Swathi, MOHAMMAD SANA, DAMERUPPULA SAI KIRAN, JADI GANESH · 5 authors
The quick rise of digital technologies has shown how blockchain could improve business operations by making them safer, more open, and less centralized. Most blockchain solutions, on the other hand, are made for big businesses, which makes it hard for small and medium-sized businesses (SMEs) to use them because they are too expensive, too complicated, and not modular. This study suggests a blockchain-based framework designed specifically for small and medium-sized businesses (SMEs) to make digital transformation more affordable. The framework includes stable consensus protocols, governance mechanisms, and important services like Decentralized Identity (DID), Zero-Knowledge Proofs (ZKP), and Digital Asset Management (DAM). It is meant to be modular, scalable, and simple to connect to current business systems. Experimental testing shows that SMEs are more efficient, secure, and easy to use. The proposed framework lowers the barriers to entry and lets small and medium-sized businesses use blockchain for new ideas, better operations, and safe online transactions.
This study analyzes 128,286 academic papers tagged as blockchain or cryptocurrency research by OpenAlex's machine-learning concept classifier, published between 2013 and mid-2026. A broader keyword search across paper abstracts identifies 1,938,409 publications that mention Web3-related terms. The analysis measures keyword frequency, temporal trajectories, growth rates, citation distributions, geographic concentration, institutional output, and open access rates. Key findings include 117x growth in annual blockchain publications between 2013 and 2025, the rise of zero-knowledge proofs as the fastest-growing cryptographic primitive (2.1x growth, 2025-2026 vs. 2022-2023), DeFi research experiencing a 74x increase from 2019 to 2025, NFT research peaking in 2023 before declining, China and India leading global output with 13.5% and 13.3% of all papers respectively, and 43.5% of all papers receiving zero citations.