This paper discusses the role of AI-driven network security solutions for cloud computing, particularly in the post-pandemic era. With the rise of remote work, AI algorithms are used to predict and mitigate network threats, ensuring safe and seamless cloud services for businesses and individuals.

John Michael Andrews, Robert Charles Bennett, Samantha Lisa Thomas, Kevin James Peterson, Elizabeth Claire Daniels

This paper explores the optimization of cloud-based healthcare data management systems, focusing on patient-centric services. By leveraging big data analytics and cloud storage, the system provides efficient data retrieval, storage, and sharing, enhancing patient care, and reducing healthcare costs in urban hospitals.

Sarah Louise Mitchell, Timothy Michael Foster, Laura Jane Clark, David Andrew Edwards, Emma Marie Harris

This paper addresses cloud-based distributed systems for real-time remote healthcare monitoring and management. By integrating wearable devices and cloud computing, the system enables healthcare providers to monitor patient vitals remotely, ensuring timely interventions and enhancing the overall quality of care for chronic patients.

James Patrick Johnson, Victoria Anne Roberts, George Richard Evans, Olivia Sarah White, Benjamin Christopher Cooper

This study presents advancements in AI-powered cloud solutions for cybersecurity in financial institutions. By applying machine learning algorithms, the system autonomously detects potential security threats and anomalies in real-time, reducing the risk of cyberattacks and enhancing data protection in cloud-based financial systems.

Michael David Young, Catherine Olivia Brown, Benjamin Thomas Harris, Emily Claire Walker, Daniel Samuel Scott

This paper proposes a comprehensive framework for leveraging cloud technology in the development of sustainable smart cities. By integrating IoT devices, big data analytics, and cloud platforms, the framework optimizes resource usage, reduces energy consumption, and ensures long-term sustainability for urban areas.

William Daniel Parker, Julia Rose Edwards, John Michael Reed, Elizabeth Marie Mitchell, Henry Joseph Cooper

This paper introduces a cloud computing-based solution for predictive analytics in healthcare systems. By analyzing historical patient data and using machine learning algorithms, the solution predicts patient outcomes, enhancing proactive decision-making in clinical settings and improving overall healthcare service delivery.

Michael Henry Davis, Sarah Ellen Scott, James Patrick Bell, Olivia Louise Harris, Benjamin Edward Parker

This paper explores emerging trends and solutions for data privacy and security in cloud computing environments. By applying advanced encryption techniques and multi-factor authentication, cloud services can ensure robust data protection and compliance with regulatory standards, addressing the growing concerns of cyber threats.

Charlotte Jane Simpson, Alexander Michael Evans, Robert Thomas Hughes, Ella Grace Parker, Daniel Alexander Wright

This paper proposes a cloud-enabled IoT framework for real-time monitoring of environmental conditions. By integrating IoT devices with cloud platforms, the system ensures continuous data collection and analysis, allowing for immediate responses to environmental changes and promoting sustainability in urban and rural areas.

David Michael Clark, Emily Rose Williams, Benjamin Andrew Smith, Olivia Claire Brown, Daniel William Taylor