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Dr. Neeti Misra is an Assistant Professor in the School of Business at UPES, Dehradun, Uttarakhand, India. Her academic interests include Artificial Intelligence, digital transformation, business analytics, cloud computing, and intelligent decision support systems. She is actively involved in interdisciplinary research integrating AI technologies with business and management applications.
Cloud computing has become a pivotal technology for the large-scale implementation of Artificial Intelligence (AI)-based prediction applications. The integration of cloud infrastructure, Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT), Big Data Analytics, and edge computing allows organisations to handle extensive amounts of real-time data, facilitating astute prediction and decision-making in sectors such as healthcare, manufacturing, finance, agriculture, transportation, smart cities, education, and industrial automation. In contrast to conventional on-premises computer systems, cloud-based AI infrastructures offer nearly boundless computational capabilities, flexible storage, decentralised processing, automated model implementation, and enhanced availability. These features provide scalable predictive analytics, smart automation, and instantaneous decision-making assistance, all while decreasing infrastructure expenses and enhancing operational efficacy. This chapter elucidates the principles, structure, cloud service paradigms, AI frameworks, predictive applications, obstacles, and prospective research trajectories of cloud-centric AI frameworks for scalable predictive applications.
The swift expansion of the Internet of Things (IoT) and cloud computing has established intricately linked digital ecosystems where billions of gadgets perpetually share data with edge nodes, cloud infrastructures, apps, and consumers. While increasing interconnectedness facilitates intelligent and scalable services, it concurrently presents considerable security issues, such as unauthorised access, identity impersonation, data manipulation, single points of failure, privacy infringements, and compromised IoT devices. Blockchain technology offers a decentralised and immutable solution for enhancing trust, authentication, data integrity, access management, and secure communication among diverse IoT and cloud ecosystems. This chapter elucidates the essential principles of blockchain-integrated IoT and cloud security, blockchain architecture, consensus protocols, smart contracts, decentralised identification, secure data transmission, access management, privacy safeguarding, and blockchain-cloud amalgamation. It further examines lightweight blockchain methodologies for resource-limited IoT devices, edge-supported blockchain frameworks, AI incorporation, real-world applications, performance indicators, obstacles, and prospective research avenues.