Quantum Synergies: Revolutionizing Security, Blockchain, and Biomedical Science with AI

The convergence of blockchain, artificial intelligence (AI), and cloud computing is catalyzing a paradigm shift in developing secure, intelligent, and scalable digital infrastructures. This triad of technologies is increasingly utilized to improve performance, transparency, and trust in engineering-driven and socio-technical environments. This study systematically reviews the evolution, integration strategies, and applications of blockchain, AI, and cloud computing in digital ecosystems. The analysis is based on 108 peer-reviewed studies spanning the years 2012 to 2025. A comprehensive literature analysis was conducted to identify trends, synergies, and sector-specific implementations of these systems. The review explores how their integration supports real-world engineering and operational use cases. Blockchain contributes to decentralized architectures, secure data exchange, and identity verification. AI supports adaptive behavior, autonomous decision-making, and predictive analytics. Cloud computing offers the scalable infrastructure necessary for deployment. Key challenges addressed include interoperability, latency, security trade-offs, and resource allocation. Use cases in digital finance, supply chain management, and industrial automation demonstrate the effectiveness of this integration in building resilient, ethically aligned, and high-performance infrastructures. The findings offer valuable insights and technical considerations for engineers and architects seeking to design next-generation cyber-physical systems that are secure, intelligent, and socially responsive. Clinical Trial Number Not applicable. This article accentuates the extensive use of blockchain, cloud computing, and AI principles, emphasizing their crucial significance in the contemporary digital environment and paths in which blockchain technology may be employed to automate financial transactions, enhance the security of personal data and records, facilitate cross-border transactions, verify identities, execute smart contracts, utilize cryptocurrencies, and manage supply chains. This research systematically assesses the development and practical application of blockchain, cloud computing, and artificial intelligence technologies over the past decade. This study primarily focuses on monitoring the progress, practical applications, and benefits of blockchain technology in the context of financial transactions. This article probes the symbiotic relationship between artificial intelligence, cloud and blockchain technology, analyzing the evolution and fundamental concepts of their integration from 2012 to 2025. This paper also presents a detailed analysis of 108 research works acquitted over the past decade. The study provides a comprehensive examination of the current state and fundamental principles related to the integration of artificial intelligence, cloud, and blockchain technology. This paper offers a comprehensive analysis of the major obstacles confronted by blockchain technology, examining its wide-ranging applications over several industries and its socko role in transaction systems and the domain of cryptocurrencies.

Integrating blockchain technology with artificial intelligence (AI) i.e., blockchain Intelligence makes an extremely powerful tool that solves many multidimensional problems in several domains. Blockchain technology has the potential to provide links to shared data, transactions, and records in a decentralized, safe, and reliable manner, including the information and decision-making capability of AI which makes machines similar as capable as humans. This study is intended to present an updated systematic review of the integration of Blockchain and AI in various application areas. We have studied and summarized more than 100 research papers to present an updated version of the review. We also discuss the future of Blockchain technologies with AI. By integrating these two technologies results increases the security, efficiency, and productivity of the applications. Past works feature a few possible advantages of integration of Blockchain and AI, yet just give a restricted hypothetical system to depict forthcoming certifiable combination instances of the two advances. We survey and orchestrate surviving exploration on the integration of AI and Blockchain are other ways around to thoroughly build up a future research plan on the fusion of the two innovations. We also proposed an agenda to develop a secure system of cyber threat intelligence information exchange by using features of blockchain and artificial intelligence. This paper mainly focusses on explaining how collaboration of blockchain and AI gives immense boost in latest domains like Cybersecurity, Healthcare, Supply Chain Management, Finance and Banking and Social Media Analytics.

The effective integration of blockchain technology and artificial intelligence (AI) has the potential to change healthcare management. Two cutting-edge developments in the healthcare industry are blockchain and artificial intelligence. Blockchain, an open network for information sharing and permission, is being used in e-Health to apply artificial intelligence models. Healthcare workers will be able to view patient medical records on the blockchain. Artificial intelligence (AI) makes use of a wide range of suggested algorithms, decision-making power, and vast amounts of data. Health care services can be made more decentralized, transparent, safe, and impenetrable with the use of blockchain technology. AI needs cryptographic records to be stored, and blockchain makes this possible. Applications of artificial intelligence in healthcare management include chatbots for diagnosis and treatment, predictive analytics, personalized medicine, and more. Blockchain technology has applications in supply chain management, clinical trial management, interoperability, and data security and integrity in healthcare management. A more effective, safe, and patient-centered healthcare ecosystem can be created by integrating blockchain technology and artificial intelligence (AI) into healthcare management. It can encourage the development of a wide range of applications in radiology, cancer treatment, cardiology, dermatology, and fundoscopy that may save patients' lives.

Artificial Intelligence (AI) is increasingly revolutionizing the food and beverage service industry by offering innovative solutions to enhance operational efficiency and personalize customer experiences. This abstract explores the transformative impact of AI technologies such as machine learning, predictive analytics, and robotics on various aspects of hospitality operations. AI-driven automation streamlines kitchen processes, optimizes inventory management, and reduces operational costs, thereby improving service consistency and profitability (Alsmadi et al., 2020; Li et al., 2021).AI facilitates personalized client interactions by analyzing vast datasets to understand individual preferences, dietary restrictions, and purchasing behaviors. This capability empowers establishments to offer tailored menu recommendations, personalized promotions, and interactive dining experiences that cater to diverse consumer needs (Chen et al., 2019; Huang et al., 2020). AI's integration into the food and beverage service industry significantly enhances customer satisfaction and loyalty while concurrently boosting revenue through targeted marketing and operational efficiencies. By leveraging AI technologies such as machine learning and predictive analytics, establishments can tailor offerings to meet individual preferences and anticipate consumer behavior, thereby fostering stronger customer relationships. Moreover, the future trajectory of AI in this sector foresees advancements in IoT integration, AR applications, and blockchain technology. These innovations are set to further transform operations by optimizing efficiency, enriching customer interactions, and ensuring robust supply chain transparency. IoT devices, for instance, will facilitate real-time data collection and analysis, thereby enhancing inventory management precision and optimizing resource allocation to meet demand fluctuations effectively. AR applications will offer immersive dining experiences, allowing customers to interact with digital menus or view culinary presentations. Blockchain technology will enhance transparency and traceability, ensuring food safety and compliance with regulatory standards. Together, these innovations will enable food and beverage establishments to innovate and differentiate themselves in a competitive market landscape, ultimately shaping the future of dining experiences worldwide to further optimize operations and enhance transparency in supply chain management (Jiang et al., 2023; Wang et al., 2023).

Abstract: The drug discovery landscape and neurodegenerative disease diagnostics are expe-riencing a paradigm shift with the integration of artificial intelligence (AI) and machine learn-ing (ML) technologies. This review provides an elaborate discussion of AI-based approaches across all stages of computer-aided drug design (CADD), including virtual screening, peptide synthesis, pharmacophore modelling, quantitative structure–activity relationships (QSAR), and drug repurposing. Particular emphasis is placed on Alzheimer's disease (AD), a multifac-eted neurodegenerative disorder, with AI enabling early diagnosis, patient stratification, and subtype classification to support precision medicine. The review highlights recent developments in supervised and unsupervised learning, omics integration, and the increasing importance of explainable AI (XAI) in addressing the “black box” limitations of traditional AI models. We categorize and assess major AI platforms and tools by their scope, stage of implementation, and form of explainability, offering a practical framework for their application in pharmaceutical and clinical research. The combined use of deep learning, quantum simulation, and virtual reality is also discussed in the context of de novo drug design, compound screening, and toxicity prediction. With con-tinued advances in AI, interdisciplinary collaboration and ethical oversight are essential to translate these digital innovations into effective, safe, and personalized therapies. This review serves as an all-encompassing guide for researchers, clinicians, and developers working at the interface of AI and drug development, particularly those addressing the unmet challenges in Alzheimer's disease. As outlined in the abstract and reflected in the article title, this review bridges AI-driven drug discovery and Alzheimer’s diagnosis, with specific empha-sis on explainable models for next-generation therapeutics. The subsequent sections expand on these themes, offering a structured synthesis of tools, applications, and methodological frameworks.

Artificial intelligence (AI) has emerged as a transformative force in pharmaceutical research, revolutionizing the traditional process of drug discovery and development. Conventional methods are lengthy, costly, and prone to high failure rates, whereas AI provides a faster, data-driven, and more efficient alternative. Through techniques such as machine learning, deep learning, and predictive analytics, AI accelerates target identification, molecular design, and lead optimization while improving safety assessments and clinical trial efficiency. Current innovations, including protein structure prediction, generative AI models, and integration of multi-omics data, are reshaping modern drug discovery by enabling the development of novel and precise therapeutics. Moreover, AI contributes to post-market surveillance by detecting adverse reactions and ensuring ongoing drug safety. Despite its remarkable potential, several challenges persist, including data quality and standardization issues, limited model interpretability, regulatory uncertainty, and ethical considerations. Addressing these barriers requires collaboration between researchers, regulators, and technology experts to ensure transparency, reproducibility, and responsible implementation. Looking ahead, the integration of AI with quantum computing, systems biology, and personalized medicine is expected to significantly enhance innovation, reduce development timelines, and increase the overall success rate of new drugs. Ultimately, AI is paving the way for a new era of intelligent, efficient, and patient-centered pharmaceutical discovery.

The integration of Artificial Intelligence (AI) and cloud computing has revolutionized enterprise systems, particularly in predictive marketing. AI-powered enterprise solutions enable businesses to analyze vast amounts of data in real-time, enhancing decision-making, customer engagement, and operational efficiency. Predictive analytics allows companies to anticipate consumer behavior, refine marketing strategies, and optimize customer interactions. Cloud computing further supports AI-driven predictive marketing by providing scalable and cost-effective solutions that enhance data processing capabilities and business intelligence. AI-integrated enterprise resource planning (ERP) and customer relationship management (CRM) systems facilitate automated decision-making, improving supply chain management and personalized marketing campaigns. Despite its advantages, AI adoption in enterprise systems and predictive marketing presents challenges such as data privacy concerns, cybersecurity risks, and ethical considerations. The complexity of AI integration requires substantial investment in infrastructure and regulatory compliance to mitigate biases and ensure transparency in AI-driven decisions. Explainable AI (XAI) is increasingly necessary to build trust and accountability in enterprise applications. Future advancements in AI, including blockchain, augmented reality (AR), and quantum computing, will enhance predictive analytics and business intelligence, further transforming marketing automation and decision-making processes. The convergence of AI and blockchain is particularly promising in securing digital transactions and improving data transparency in enterprise operations. As AI continues to reshape enterprise systems and predictive marketing, businesses must adopt responsible AI practices, strengthen cybersecurity measures, and comply with global regulations to maximize its benefits. Companies that leverage AI-driven insights will gain a competitive edge by improving customer engagement, optimizing marketing strategies, and driving sustainable growth in the evolving digital economy.

The advent of quantum computing poses significant threats to traditional cybersecurity systems, which rely on cryptographic algorithms vulnerable to quantum attacks. This research explores the utilization of artificial intelligence (AI) in designing a prototype cybersecurity system aimed at countering the emerging threats of quantum computing. The study integrates AI-based intrusion detection systems with quantum-resistant cryptographic techniques to enhance the security of digital systems against quantum-driven cyberattacks. A combination of machine learning algorithms, such as neural networks and decision trees, is employed to detect and mitigate potential cybersecurity breaches. Additionally, post-quantum cryptography (PQC) is incorporated to safeguard sensitive data against the capabilities of quantum computers. The results indicate that the proposed system outperforms conventional cybersecurity methods in detecting threats with greater speed and accuracy, while also providing robust protection against quantum-enabled attacks. Moreover, the integration of AI allows for adaptive and proactive defense mechanisms, improving the overall system resilience. The study concludes that combining AI with post-quantum cryptography offers a promising solution to secure digital infrastructures in the face of quantum computing advancements, marking a significant step toward future-proofing cybersecurity strategies.

The rapid evolution of financial technology (fintech) platforms has exponentially increased the volume and sophistication of financial transactions, concurrently elevating the risk and complexity of fraudulent activities. This necessitates a paradigm shift in fraud detection methodologies towards more agile, accurate, and predictive solutions. This paper presents a comprehensive study on the transformative potential of advanced Artificial Intelligence (AI) algorithms in enhancing fintech fraud detection mechanisms. By leveraging cutting-edge AI techniques including deep learning, machine learning, and natural language processing, this research aims to develop a robust fraud detection framework capable of identifying, analyzing, and preventing fraudulent transactions in real-time. Our methodology encompasses the deployment of several AI algorithms on extensive datasets comprising genuine and fraudulent financial transactions. Through a comparative analysis, we identify the most effective algorithms in terms of accuracy, efficiency, and scalability. Key findings reveal that deep learning models, particularly those employing neural networks, outperform traditional machine learning models in detecting complex and nuanced fraudulent activities. Furthermore, the integration of natural language processing enables the extraction and analysis of unstructured data, significantly enhancing the detection capabilities. Conclusively, this paper underscores the critical role of advanced AI algorithms in revolutionizing fintech fraud detection. It highlights the superior performance of AI-based models over conventional methods, offering fintech platforms a more dynamic and predictive approach to fraud prevention. This research not only contributes to the academic discourse on financial security but also provides practical insights for fintech companies striving to safeguard their operations against fraud. Keywords: Artificial Intelligence, Fintech, Fraud Detection, Ethical Ai, Regulatory Compliance, Data Privacy, Algorithmic Bias, Predictive Analytics, Blockchain Technology, Quantum Computing, Interdisciplinary Collaboration, Innovation, Transparency, Accountability, Continuous Learning, Ethical Principles, Real-Time Processing, Financial Sector.

Quantum computing (QC) is not a futuristic notion in agriculture, though its full potential has yet to be realized. QC is an emerging field at the intersection of physics and computer science that holds immense potential to revolutionize various sectors, including agriculture production and artificial intelligence (AI) modeling. While QC is still in the early stages of development and practical applications within agriculture are not yet widespread, researchers are actively exploring its potential benefits in various agricultural domains, including crop optimization, livestock breeding, and environmental monitoring. QC harnesses the principles of quantum mechanics to perform computations using quantum bits or qubits, which can exist in multiple states simultaneously. Unlike classical computers, which rely on binary bits representing 0 or 1, quantum computers exploit phenomena such as superposition and entanglement to process information in parallel, potentially offering exponential speedup for certain types of problems. In agriculture production, particularly in animal science, QC offers promising avenues for optimizing processes and enhancing productivity. Quantum algorithms can analyze vast amounts of genomic data to improve breeding programs, leading to the development of more resilient and productive livestock breeds. Furthermore, QC can facilitate precision farming techniques by modeling complex environmental factors and animal behavior to optimize feeding strategies, disease management, and overall farm management practices. Moreover, QC can significantly benefit AI modeling by accelerating computations and enabling more efficient training of AI models. Quantum algorithms can enhance the performance of AI algorithms in various tasks, including pattern recognition, natural language processing, and predictive analytics. By leveraging quantum-enhanced optimization algorithms, AI models can achieve better convergence and accuracy, leading to more effective decision-making and problem-solving capabilities. While hybrid intelligent models also represent a novel frontier in agriculture, QC has the potential to expedite the merging of mechanistic and AI modeling paradigms, facilitating a more holistic understanding of complex systems in agriculture and beyond. By integrating mechanistic models, which describe the underlying physical processes, with AI models, which learn patterns from data, quantum computing can enable comprehensive simulations and predictions of agricultural systems. This fusion of modeling paradigms can lead to more accurate and robust predictions of crop yields, livestock performance, and environmental impacts, facilitating informed decision-making for farmers and policymakers. The application of QC in agriculture, however, requires interdisciplinary collaborations between physicists, computer scientists, agronomists/animal scientists, and AI researchers. These collaborations can drive the development of quantum algorithms tailored to agricultural applications, the integration of quantum-enhanced AI techniques into existing modeling frameworks, and the deployment of QC resources in real-world agricultural systems. Ultimately, harnessing the power of QC holds the potential to revolutionize agriculture production practices, including regenerative agriculture, and advance AI modeling capabilities, paving the way for a more sustainable and efficient agricultural industry.

The integration of artificial intelligence (AI) in education has the potential to revolutionize teaching and learning, particularly in the development of students’ critical thinking skills. This study explores science instructors' familiarity, perceptions, and experiences with using AI to enhance students' critical thinking skills, as well as the level of institutional support for AI integration in teaching. A quantitative survey was conducted among 20 science instructors from higher education institutions in Isabela, Philippines. The findings reveal that while instructors acknowledge AI's potential to improve educational outcomes, there is a significant gap in formal AI training and literacy among educators. Positive correlations were found between AI literacy, AI integration, and critical thinking development, suggesting that as AI literacy increases, AI integration and enhancement of critical thinking skills also increase. Regression analysis identified AI integration as a significant predictor of critical thinking development. Challenges remain in the effective implementation of AI, including concerns about overreliance on AI-generated responses and the need for clear assessment guidelines. Interestingly, years of teaching experience did not significantly influence participants’ AI literacy, perceptions, or integration. This study highlights the importance of developing comprehensive AI literacy programs for educators and integrating AI into curriculum structures to balance AI-enhanced learning with human-centered pedagogy. These findings emphasize the need for thoughtful implementation and ongoing research to effectively leverage AI in promoting critical thinking skills in science education.

A roadmap from classical cryptography to post-quantum resistant cryptography for 5G-enabled IoT: Challenges, opportunities and solutions

<p>In the rapidly evolving technological landscape, modern innovations such as blockchain (BC), artificial intelligence (AI), and the Internet of Things (IoT) are playing a pivotal role in realizing the vision of Society 5.0. This concept envisions a harmonious integration of physical, digital, and human elements to create a sustainable and progressive future. Emerging technologies like robotics, biotechnology, quantum computing, 5G/6G networks, smart cities, and the metaverse are expected to further amplify the impact of Society 5.0, driving transformative changes across industries and societal structures. The integration of BC, AI, and IoT within cloud-based frameworks offers a robust solution to enhance security, privacy, and data management. The integration of blockchain, AI, and IoT within a cloud-based framework offers a transformative solution to address the challenges of modern societies. By leveraging these technologies, the proposed platform aims to create a secure, efficient, and sustainable ecosystem that enhances quality of life and drives progress toward the vision of Society 5.0. This approach not only tackles current societal issues but also paves the way for a more interconnected and innovative future. This article introduces a platform that seamlessly combines these technologies to provide a secure and reliable foundation for data collection, sharing, and analysis while enabling the development of smart applications that improve efficiency, productivity, and overall quality of life (QoL).</p>

The integration of artificial intelligence (AI) and blockchain technology in curatorial practice offers transformative potential for managing, presenting, and distributing both traditional and digital art. This study explores how AI enhances curatorial processes through advanced data analysis and personalized visitor experiences. AI assists curators in organizing collections and recommending artworks tailored to individual preferences, fostering greater engagement with dynamic, customized exhibitions. Blockchain technology, on the other hand, ensures the provenance of decentralized artworks, guaranteeing authenticity and transparency. It addresses issues like counterfeiting, ownership disputes, and secure transactions, while supporting artists through smart contracts that ensure equitable compensation. However, ethical concerns remain. These include biases in AI algorithms, intellectual property challenges in decentralized NFT platforms, and limited digital access for marginalized artists. Academic studies and case analyses underscore these challenges and advocate for collaboration among curators, artists, technologists, and policymakers. This approach seeks to resolve ethical dilemmas, promote inclusivity, and maintain cultural integrity in implementing these technologies. The study emphasizes the need for public policy frameworks to regulate AI and blockchain, ensuring fair compensation and equitable access to their benefits while safeguarding cultural values. By addressing these concerns, these technologies can unlock new possibilities for the art world. Transformasi Praktik Kuratorial: Peran AI dan Blockchain dalam Membentuk Paradigma Seni-Sains yang Etis untuk Kebijakan Publik Abstrak Integrasi kecerdasan buatan (AI) dan teknologi blockchain dalam praktik kuratorial menawarkan potensi transformatif untuk mengelola, menyajikan, dan mendistribusikan seni baik tradisional maupun digital. Studi ini mengeksplorasi bagaimana AI meningkatkan proses kuratorial melalui analisis data yang mutakhir dan pengalaman pengunjung yang dipersonalisasi. AI membantu kurator dalam mengatur koleksi dan merekomendasikan karya seni yang disesuaikan dengan preferensi individu, mendorong keterlibatan yang lebih besar dengan pameran yang dinamis dan disesuaikan. Di sisi lain, teknologi blockchain memastikan asal-usul karya seni yang terdesentralisasi, menjamin keaslian dan transparansi. Teknologi ini mengatasi masalah seperti pemalsuan, sengketa kepemilikan, dan transaksi yang aman, serta mendukung para seniman melalui kontrak pintar yang memastikan kompensasi yang adil. Akan tetapi, masalah etika tetap ada. Ini termasuk bias dalam algoritma AI, tantangan kekayaan intelektual dalam platform NFT yang terdesentralisasi, dan akses digital yang terbatas untuk seniman yang terpinggirkan. Studi akademis dan analisis kasus menggarisbawahi tantangan-tantangan ini dan mengadvokasi kolaborasi di antara kurator, seniman, ahli teknologi, dan pembuat kebijakan. Pendekatan ini berusaha untuk menyelesaikan dilema etika, mempromosikan inklusivitas, dan menjaga integritas budaya dalam mengimplementasikan teknologi ini. Studi ini menekankan perlunya kerangka kerja kebijakan publik untuk mengatur AI dan blockchain, memastikan kompensasi dan akses yang adil terhadap manfaatnya sambil menjaga nilai-nilai budaya. Dengan mengatasi masalah ini, teknologi ini dapat membuka peluang baru bagi dunia seni.

This article explores the transformative potential of integrating artificial intelligence (AI) into blockchain technology and the cryptocurrency market. Highlighting the growing attention towards blockchain and cryptocurrencies, emphasizing their decentralized, secure, and transparent nature. However, challenges, including the need to address scalability issues and ensure responsible usage, prompt a focus on AI integration as a viable solution. The study delves into the benefits of AI in the cryptocurrency market, showcasing its ability to predict trends, identify risks, and optimize trading strategies. The research emphasizes the relevance of investigating the integration of AI into blockchain and its specific applications, particularly in detecting and preventing fraud. The article recognizes the potential for increased efficiency, reduced costs, and improved security in transactions through this integration. Acknowledging potential challenges such as AI decision-making implications and technical hurdles, the article advocates for ongoing research and development. It highlights the need for responsible AI adoption to maximize benefits while addressing concerns like algorithmic biases and potential market manipulation. Also explores AI's role in risk management, fraud detection, and investment management within the financial sector. It underscores the importance of ethical considerations, transparency, and accountability to ensure AI's integration aligns with the best interests of all stakeholders. As the article concludes, it emphasizes the dynamic and transformative potential of the integration of AI into blockchain and the cryptocurrency market. It advocates for a collaborative approach among stakeholders, policymakers, and developers to ensure responsible usage, compliance with regulations, and ongoing innovation. The synthesis of AI and blockchain technologies has the potential to revolutionize industries, enhance security, and contribute to a more efficient, transparent, and innovative future.