Comprehensive resource describing how operations, outputs, and offerings of the oil and gas industry can improve via advancements in AI The Power of Artificial Intelligence for the Next-Generation Oil & Gas Industry describes the proven and promising digital technologies and tools available to empower the oil and gas (O & G) industry to be future-ready. It shows how the widely reported limitations of the oil and gas industry are being nullified through the application of breakthrough digital technologies and how the convergence of digital technologies helps create new possibilities and opportunities to take this industry to its next level. The text demonstrates how scores of proven digital technologies, especially in AI, are useful in elegantly fulfilling complicated requirements such as process optimization, automation and orchestration, real-time data analytics, productivity improvement, employee safety, predictive maintenance, yield prediction, and accurate asset management for the O & G industry. The text differentiates and delivers sophisticated use cases for the various stakeholders, providing easy-to-understand information to accurately utilize proven technologies towards achieving real and sustainable industry transformation. The Power of Artificial Intelligence for the Next-Generation Oil & Gas Industry includes information on: <ul> <li>How various machine and deep learning (ML/DL) algorithms, the prime modules of AI, empower AI systems to deliver on their promises and potential</li> <li>Key use cases of computer vision (CV) and natural language processing (NLP) as they relate to the O & G industry</li> <li>Smart leverage of AI, the Industrial Internet of Things (IIoT), cyber physical systems, and 5G communication</li> <li>Event-driven architecture (EDA), microservices architecture (MSA), blockchain for data and device security, and digital twins</li> </ul> Clearly expounding how the power of AI and other allied technologies can be meticulously leveraged by the oil and gas industry, The Power of Artificial Intelligence for the Next-Generation Oil & Gas Industry is an essential resource for students, scholars, IT professionals, and business leaders in many different intersecting fields.

The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry: Envisaging AI-inspired Intelligent Energy Systems and Environments (IEEE Press Series on Power and Energy Systems)

Computers & Technology

Chelliah, Pethuru Raj

Jayasankar, Venkatraman

Agerstam, Mats

Sundaravadivazhagan, B.

Cyriac, Robin

Computer Science

Wiley-IEEE Press

Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: <ul> <li>Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problems</li> <li>Generating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablers</li> <li>Compressing AI models so that computational, memory, storage, and network requirements can be substantially reduced</li> <li>Addressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous data</li> <li>Overcoming cyberattacks on mission-critical software systems by leveraging federated learning</li> </ul>

Model Optimization Methods for Efficient and Edge AI: Federated Learning Architectures, Frameworks and Applications

Colby, Robert

Rahmani, Amir Masoud

Nagasubramanian, Gayathri

Ranganath, Sunku

Essentials of Cloud Computing: A Holistic Perspective (Texts in Computer Science)

Surianarayanan, Chellammal

Web Development & Design

Springer

Numerous advancements are being brought in and incorporated into the cloud domain with the aim of realizing a trove of deeper and decisive automations. Rather than discussing the cloud paradigm in isolation, this fully updated text examines how cloud computing can work collaboratively with other computing models to meet the needs of evolving trends.This multi-dimensional approach encompasses the challenges of fulfilling the storage requirements of big data, the use of the cloud as a remote server for Internet of Things and sensor networks, and an investigation of how cloud computing is interlinked with other established computing phenomenon such as edge computing.&nbsp;New chapters&nbsp;illustrate the distinct ideals of the cloud-native computing, proclaimed as the next-generation cloud computing paradigm. Topics and features: <ul> <li>Includes learning objectives, motivating questions, and self-test exercises</li> <li>Introduces the underlying concepts, fundamental features, and key technological foundations of cloud computing</li> <li>Examines how enterprise networking and cloud networking can work together to achieve business goals</li> <li>Reviews the different types of cloud storage available to address the evolution of data and the need for digitization</li> <li>Discusses the challenges and approaches to implementing cloud governance, security, and the hot topic of cloud management</li> <li>Describes the details of cloud migration, the crucial role of monitoring in optimizing the cloud, and the basics of disaster recovery using cloud infrastructure</li> </ul> This technically rigorous, yet simple-to-follow textbook is an ideal resource for graduate courses on cloud computing. Professional software developers and cloud architects will also find the work to be an invaluable reference.

Essentials of Cloud Computing: A Holistic, Cloud-Native Perspective (Texts in Computer Science)

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Books by Chelliah, Pethuru Raj