This paper focuses on optimizing cloud-based healthcare systems by integrating AI and big data analytics for real-time diagnostics. The system improves decision-making and operational efficiency by processing large healthcare datasets, providing predictive insights for clinicians and ensuring timely interventions for patients.

Lucas Nathaniel Carter, Maya Isabelle Stewart, William Henry King, Sophia Amelia Clarke, Daniel George Bennett

This study introduces blockchain technology in the development of smart grids, aiming to enhance energy distribution and consumption efficiency. The proposed blockchain-based solution ensures secure, transparent, and decentralized energy transactions, promoting more effective energy usage and supporting sustainable energy initiatives globally.

David Matthew Cooper, Ethan Lucas Williams, Grace Isabella Miller, Noah Benjamin Moore, Olivia Charlotte Young

This research examines how edge computing can enhance the efficiency and responsiveness of autonomous vehicle systems by enabling real-time data processing. By offloading computation to edge devices, vehicles can process sensor data locally, reducing latency and improving decision-making capabilities for safe navigation.

Matthew Alexander Thompson, Amelia Sophia Mitchell, Isaac Samuel Williams, Lily Grace Johnson, Noah Jacob Carter

This paper proposes a blockchain-based security framework to ensure the privacy and integrity of data in cloud computing services. By utilizing decentralized consensus mechanisms, the framework provides a secure environment for data transactions, enhancing trust and reducing the risk of cyberattacks on sensitive cloud systems.

Chloe Elizabeth Martin, Daniel Lucas Walker, Alexander James Turner, Eva Olivia Evans, Benjamin Jack Lee

This research explores the application of artificial intelligence (AI) for real-time fraud detection in financial transactions processed over cloud networks. By leveraging machine learning algorithms, the system can detect fraudulent patterns and prevent financial losses, ensuring secure and trustworthy online transactions.

Henry Thomas Williams, Olivia Grace Scott, Ethan Robert Harris, Sophia Mia Davis, William Alexander Moore

This paper presents the potential of quantum computing to optimize large-scale cloud infrastructure, especially in the context of big data. By leveraging quantum algorithms, cloud providers can enhance computational efficiency, reduce latency, and accelerate data processing, paving the way for more efficient cloud-based solutions.

Jacob William Harris, Amelia Rose Green, Lucas Charles Brown, Isabella Ava White, Elijah Samuel Clark

This paper explores the integration of blockchain and IoT technologies in securing healthcare data on cloud platforms. The proposed system ensures data privacy, real-time monitoring, and transparent records, empowering healthcare professionals to securely manage patient information in a highly reliable and scalable environment.

James Matthew Williams, Emma Olivia Brown, Alexander James Smith, Charlotte Isabella Miller, Daniel Joseph Davis

This research investigates the integration of cloud-based edge computing for autonomous vehicle systems. By utilizing edge nodes within the cloud network, real-time data processing and decision-making capabilities are enhanced, enabling faster response times and improving the overall safety and efficiency of autonomous driving systems.

Noah Benjamin Wilson, Ava Sophia Johnson, Liam Daniel Davis, Mia Harper Thompson, Elijah David Garcia