The Impact of Artificial Intelligence in Banking Sector
Secure Med: Enhancing Patient Privacy and Care through Blockchain
A Proposed Model for Improving the Reliability of Online Exam Results using Blockchain
A Scalable IoT Solution for Real-Time Data Collection and Cloud Integration
Drug Tracing in the Healthcare Supply Chain using Distributed Ledger Technology
Music Tutor: A Personalized and Interactive Learning Platform using Firebase and React
A Comprehensive Review of Security Issues in Cloud Computing
Data Quality Evaluation Framework for Big Data
An Extended Min-Min Scheduling Algorithm in Cloud Computing
Be Mindful of the Move: A Swot Analysis of Cloud Computing Towards the Democratization of Technology
An Architectural Framework for Ant Lion Optimization-based Feature Selection Technique for Cloud Intrusion Detection System using Bayesian Classifier
GridSim Installation and Implementation Process
A Survey on Energy Aware Job Scheduling Algorithms in Cloud Environment
Genetic Algorithm Using MapReduce - A Critical Review
Clustering based Cost Optimized Resource Scheduling Technique in Cloud Computing
Encroachment of Cloud Education for the Present Educational Institutions
This paper explores the transformative role of Artificial Intelligence (AI) in the banking sector and a comprehensive understanding of how AI is reshaping banking operations, enhancing customer experiences, and driving financial innovation. It explores the multidimensional impacts of Artificial Intelligence on the banking sector, focusing on customer experience, risk management, operational efficiency, challenges, and future prospects. Through a comprehensive literature review and thematic analysis, the current study examines how AI technologies enhance customer interactions by providing personalized and efficient services. The incorporation of AI in the management of risk is analyzed, and operational efficiency is scrutinized, with AI-driven automation leading to cost reductions and improved service delivery. It also addresses the challenges associated with AI adoption, including ethical concerns, data privacy issues, and the need for regulatory frameworks. The outcomes of the research highlight the transformative budding of AI in reshaping the banking landscape, advocating for a balanced approach that leverages AI's benefits while addressing its challenges. This study also contributes valuable insights for stakeholders aiming to harness AI's capabilities to drive growth and to the understanding and the advancement of AI applications and the innovation in the banking industry.
In today's dynamic healthcare environment, protecting patient privacy, securing sensitive data, and maintaining the integrity of medical records are more critical than ever. Traditional healthcare systems typically face issues like data breaches, limited accessibility, and outdated record-keeping practices that compromise patient information. Secure Med introduces a transformative solution by leveraging blockchain technology, a decentralized, tamper-resistant infrastructure that ensures data is secure, transparent, and efficiently managed. Patient records are encrypted and distributed across a secure ledger, accessible only to authorized professionals with explicit patient consent. Smart contracts and encryption protocols provide patients with complete control over their medical data. This system enhances data accuracy, real-time accessibility, and impenetrable security, enabling faster, more accurate diagnoses and improved decision-making, especially during emergencies. Secure Med thus reinforces the resilience of healthcare systems while empowering individuals to manage their personal data, ensuring privacy and autonomy at every stage of care.
Learning Management Systems (LMS) have seen a surge in popularity, especially during the COVID-19 pandemic, due to their ability to enhance educational efficiency and effectiveness. Among LMS features, online exams have become essential for evaluating students' understanding and academic performance, significantly influencing their progression. However, ensuring the transparency and reliability of online exam results is crucial, as vulnerabilities like hacking can negatively affect students' grades. Traditional online exam systems frequently rely on centralized databases such as MySQL, which are prone to unauthorized access and data manipulation. This paper introduces a blockchain based framework designed to securely conduct and evaluate academic exams in a peer-to-peer environment. By leveraging hashing techniques to maintain data integrity and implementing a proof-of-stake mechanism for added security, the framework addresses key vulnerabilities found in conventional systems. Blockchain's decentralized structure and cryptographic hashing of each block provide a robust solution for safeguarding exam data.
The Internet of Things (IoT) has revolutionized how devices collect, transmit, and analyze data across diverse domains such as agriculture, healthcare, and smart cities. This paper presents a scalable IoT web application designed for real- time data monitoring, analysis, and cloud integration. The system uses Angular for the frontend, Node.js for the backend, and integrates Firebase and InfluxDB for cloud-based data storage. Data from IoT sensors (temperature, motion, humidity) is transmitted through MQTT and WebSocket protocols for low-latency communication. The system supports real-time visualization, threshold-based alerts, and predictive analytics using machine learning models. This solution emphasizes modularity, data security (TLS/SSL encryption and RBAC), and adaptability, making it suitable for high- demand, multi-device environments. Challenges such as device interoperability, latency, and data reliability are addressed through edge computing, event-driven architecture, and sensor calibration. The results confirm strong performance, scalability, and usability, positioning this solution as a robust platform for real-world IoT applications.
Traditional systems are typically unreliable and prone to fraud, putting patient safety at risk. To solve these issues, this work proposes a blockchain-based drug tracing system that improves security, trust, and efficiency. This paper examines the use application of Distributed Ledger Technology (DLT), particularly blockchain, to improve drug traceability in the healthcare distribution network. Blockchain technology ensures immutability, transparency, and decentralization, allowing stakeholders to securely track drugs from manufacturing to end-user consumption. Results indicate that blockchain-based supply chains improved drug traceability with an accuracy of up to 92, significantly reducing the risk of counterfeit drug infiltration. Distributed Ledger Technology (DLT) ensures secure and transparent drug traceability by providing tamper-proof recordkeeping, real-time tracking, and stakeholder verification. This greatly minimizes counterfeit drug risks and strengthens trust in the pharmaceutical distribution network.
The Music Tutor initiative is a cloud-enabled, web-based application developed to transform traditional Carnatic music education into a digitally accessible format. Unlike conventional methods that require face-to-face interactions, this platform allows for anytime, anywhere learning by offering students and tutors a shared digital space to interact, practice, and grow musically. Built entirely using React on both frontend and backend components, and utilizing Firebase for its database and authentication services, the system emphasizes real-time responsiveness, user-role segregation, and cloud scalability.
