This paper explores the design of scalable cloud computing infrastructures optimized for large-scale data analytics. By employing distributed computing frameworks and parallel processing techniques, the proposed architecture improves efficiency, reduces latency, and enables real-time data analysis for big data applications in diverse sectors.

Henry Albert Turner, Sophie Isabel Clark, Benjamin Richard Hall, Lillian Grace Mitchell, Thomas Samuel Johnson

This research investigates the integration of edge computing with cloud platforms to enable real-time decision-making in IoT systems. The hybrid approach facilitates processing at the network edge, reducing latency, and enhances the overall system's responsiveness, making it ideal for applications like autonomous vehicles and smart cities.

Olivia Sarah Campbell, George Nathaniel Turner, Emily Grace Johnson, Jacob David Peterson, Lily Maria Brown

This paper discusses how cloud services can be leveraged to enhance smart agriculture and precision farming. By integrating IoT sensors, AI-based data analytics, and cloud computing, the system offers farmers real-time insights into crop health, soil conditions, and weather forecasts, optimizing agricultural operations.

Jacob Thomas Mitchell, Victoria Elizabeth Carter, Lucas Gabriel Harris, Charlotte Anna Lewis, George Matthew Davis

This paper explores cloud-based data management systems designed for secure healthcare record keeping. The system integrates encryption techniques and distributed storage, ensuring patient privacy and compliance with regulatory requirements while providing healthcare professionals with easy and secure access to patient data across locations.

Alexander James Harris, Sophia Rose Lee, Ethan William Thompson, Emma Louise Jackson, Noah David Brown

This research focuses on optimizing cloud storage solutions to handle high-volume, high-velocity data generated by smart city applications. By utilizing distributed cloud storage architectures and implementing dynamic data partitioning, the system supports the storage and processing of vast amounts of real-time data from urban infrastructure.

Michael Christopher Johnson, Amelia Olivia Anderson, Daniel Thomas Wilson, Lily Caroline White, Thomas Samuel Garcia

This study explores the application of decentralized cloud networks for managing healthcare data securely. The proposed system leverages blockchain and edge computing to ensure patient privacy, real-time access, and interoperability between health systems, all while adhering to strict regulations and improving data integrity.

Andrew James Clark, Katherine Maria Scott, Theodore Richard Turner, Sophie Olivia Adams, Lucas Thomas Anderson

This paper investigates the integration of edge computing and cloud technologies for real-time IoT data processing in smart cities. The framework enables efficient data collection, processing, and analysis from connected devices, enhancing city infrastructure, resource management, and providing intelligent insights for urban planning.

Daniel William Thomas, Sarah Elizabeth Miller, Lucas Benjamin Harris, Emma Grace Watson, Joseph Michael Phillips