Gagangeet Singh Aujla – författare

Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book:Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutionsPoints to the solutions provided by machine learning to optimize the grids within a smart city set-upDiscusses relevant IoE design principles and architectureHelps to automate various services in smart cities for energy managementIncludes case studies to show the effectiveness of the discussed schemes

Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book:Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutionsPoints to the solutions provided by machine learning to optimize the grids within a smart city set-upDiscusses relevant IoE design principles and architectureHelps to automate various services in smart cities for energy managementIncludes case studies to show the effectiveness of the discussed schemes

This book provides comprehensive discussion on key topics related to the usage and deployment of software defined networks (SDN) in Internet of Everything applications like, healthcare systems, data centers, edge/fog computing, vehicular networks, intelligent transportation systems, smart grids, smart cities and more.

This book provides comprehensive discussion on key topics related to the usage and deployment of software defined networks (SDN) in Internet of Everything applications like, healthcare systems, data centers, edge/fog computing, vehicular networks, intelligent transportation systems, smart grids, smart cities and more.

This book provides comprehensive discussion on key topics related to the usage and deployment of AI in urban transportation systems including drones. The deployment models for AI-based CPS are also included with an aim towards the design of interoperable and intelligent CPS architectures by researchers in future.

This book provides comprehensive discussion on key topics related to the usage and deployment of AI in urban transportation systems including drones. The deployment models for AI-based CPS are also included with an aim towards the design of interoperable and intelligent CPS architectures by researchers in future.

These two volumes constitute the revised selected papers of First International Conference, ICAIoT 2023, held in Chandigarh, India, during March 30–31, 2023.The 47 full papers and the 10 short papers included in this volume were carefully reviewed and selected from 401 submissions.

These two volumes constitute the revised selected papers of First International Conference, ICAIoT 2023, held in Chandigarh, India, during March 30–31, 2023.The 47 full papers and the 10 short papers included in this volume were carefully reviewed and selected from 401 submissions.

This book introduces readers to big data analytics. It covers the background to and the concepts of big data, big data analytics, and cloud computing, along with the process of setting up, configuring, and getting familiar with the big data analytics working environments in the first two chapters. The third chapter provides comprehensive information on big data processing systems - from installing these systems to implementing real-world data applications, along with the necessary codes. The next chapter dives into the details of big data storage technologies, including their types, essentiality, durability, and availability, and reveals their differences in their properties. The fifth and sixth chapters guide the reader through understanding, configuring, and performing the monitoring and debugging of big data systems and present the available commercial and open-source tools for this purpose. Chapter seven gives information about a trending machine learning, Bayesian network: a probabilistic graphical model, by presenting a real-world probabilistic application to understand causal, complex, and hidden relationships for diagnosis and forecasting in a scalable manner for big data. Special sections throughout the eighth chapter present different case studies and applications to help the readers to develop their big data analytics skills using various big data analytics frameworks.The book will be of interest to business executives and IT managers as well as university students and their course leaders, in fact all those who want to get involved in the big data world.