This paper investigates optimizing cloud resources for real-time video streaming applications in smart cities. The proposed model efficiently allocates computational and network resources, ensuring low latency and high availability for large-scale video surveillance and public safety monitoring systems.

Alexander Robert White, Emily Grace Lewis, Daniel Anthony Clark, Sophia Lily Mitchell, Max Gabriel Stewart

This research focuses on the integration of cloud computing with distributed AI systems for industrial automation. The study explores how cloud platforms can enable real-time data processing, predictive analytics, and autonomous decision-making to optimize manufacturing processes and improve system reliability.

Jack Daniel Carter, Olivia Sarah Bennett, Benjamin Thomas Hill, Isabella Victoria Wright, Nathan Samuel Harris

This paper proposes the use of blockchain technology to enhance security in cloud-based medical record systems. By integrating decentralized ledgers, the system ensures data integrity, prevents unauthorized access, and enables transparent tracking of medical data exchanges, offering a robust solution to health data security challenges.

James Oliver Peterson, Emma Natalie Richards, Lucas Edward King, Olivia Sophie Turner, William Henry Cooper

This paper explores the application of data analytics in cloud computing for optimizing resource allocation in smart grids. The research outlines methods for predicting power consumption, enhancing grid stability, and minimizing energy loss using cloud-based analytics, making smart grids more efficient and reliable.

Charlotte Abigail Nelson, Jack Michael Carter, Amelia Rose Taylor, William Oliver Green, Sophia Mary Edwards

This research introduces a cloud-based real-time traffic management system using IoT devices. By collecting and analyzing data from traffic sensors, the system optimizes traffic flow, reduces congestion, and improves urban mobility. The integration of cloud computing allows for real-time monitoring and decision-making.

Jacob Thomas Lewis, Charlotte Megan Mitchell, Oliver Edward Parker, William Samuel Harris, Emma Sophia Scott

This paper presents an optimization framework for cloud storage systems in healthcare, focusing on large-scale distributed data processing. The proposed solution enhances data retrieval speeds, minimizes latency, and ensures scalability, improving access to medical records and optimizing patient data management across healthcare facilities.

Benjamin Arthur Walker, Isabella Chloe Fisher, Noah Samuel Harris, Olivia Grace Mitchell, Lucas Jonathan Thomas

This research explores the integration of cloud-based big data analytics for predictive maintenance in manufacturing systems. The proposed framework enables real-time monitoring of equipment health, predictive failure analysis, and cost-effective maintenance scheduling, thus improving operational efficiency and reducing downtime in manufacturing plants.

Lucas Robert Brooks, Sophia Lily Green, Michael Henry Clark, Chloe Olivia Turner, Benjamin Peter Cooper

This paper discusses cloud-based IoT solutions for smart agriculture, focusing on crop monitoring and environmental data collection. The system uses IoT sensors to gather data on soil conditions, weather patterns, and plant health, with cloud computing enabling real-time analytics and decision-making for improved agricultural practices.

Daniel Lucas Mitchell, Natalie Sophia Lewis, Jack Edward Harris, Emma Rachel Bennett, Olivia Charlotte Thompson