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Full Description
This book discusses the effect that artificial intelligence (AI) and Internet of Things (IoT) have on industry. The authors start by showing how the application of these technologies has already stretched across domains such as law, political science, policy, and economics and how it will soon permeate areas of autonomous transportation, education, and space exploration, only to name a few. The authors then discuss applications in a variety of industries. Throughout the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises. This book provides relevant theoretical frameworks and the latest empirical research findings in various applications. The book is written for professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society, that is, trust at the level of the global economy, of networks and organizations, of teams and work groups, of information systems and, finally, trust at the level of individuals as actors in the networked environments.
Presents research in various industries and how artificial intelligence and Internet of Things is changing the landscape of business and management;
Includes new and innovative features in artificial intelligence and IoT that can help in raising economic efficiency at both micro and macro levels;
Examines case studies with tried and tested approaches to resolution of typical problems in each application of study.
Contents
Introduction.- Part I.- Data analytics for distributed computing and IoT.- Innovations in Software Requirements Engineering for IoT and Big Data.- Innovations in Software Design and Architectures of IoT and Big Data Platforms.- Data storage channels and distributed storage networks.- Big data practices and applications.- Big data retrieval, processing, analysis, and analytics.- IoT and pharmacocybernetics.- IoT for smart manufacturing (industry 4.0) and smart spaces.- IoT big data and predictive analysis.- Managing big data models with interactive Machine learning techniques.- Managing big data models with interactive Deep learning techniques.- Machine learning, data mining, web mining, and graph mining for social network analysis.- Part II.- Mobile networking and computing for cloud and fog/edge computing.- Security and Privacy Approaches to IoT and Big Data Applications and Platforms.- Virtualization of storage, networking, and computing.- SDN-enabled cloud data centers.- Elasticityand scalability of cloud resources.- Cloud management, orchestration, and automation.- Server less computing and FaaS.- Cloud-based storage platforms.- Decentralized storage in cloud and fog/edge computing systems.- Software-defined storage.- Part III.- Decentralized applications (Exchanges, Mining Pools, Trading Platforms).- Blockchain technology for developing countries.- Scalability, sharding, and scalable services for blockchain systems.- Security and privacy in the cloud and fog/edge infrastructure, services and storage.- Big Data and blockchain technology.- Cloud based authentication and privacy mechanisms Part IV.- Agile Software Engineering Approaches to IoT and Big Data Applications.- Software Engineering Framework for IoT.- Software Engineering Framework for Big Data.- Big Data Algorithms and Applications.- IoT design and architectures.- Security and Privacy Approaches to IoT and Big Data Applications and Platforms.- Conclusion.
