Arun Solanki – författare

This new volume, Cognitive Computing Systems: Applications and Technological Advancements, explores the emerging area of artificial intelligence that encompasses machine self-learning, human-computer interaction, natural language processing, data mining and more. It introduces cognitive computing systems, highlights their key applications, discusses the technologies used in cognitive systems, and explains underlying models and architectures.

Focusing on scientific work for real-world applications, each chapter presents the use of cognitive computing and machine learning in specific application areas. These include the use of speech recognition technology, application of neural networks in construction management, elevating competency in education, comprehensive health monitoring systems, predicting type 2 diabetes, applications for smart agricultural technology, human resource management, and more.

With chapters from knowledgeable researchers in the area of artificial intelligence, cognitive computing, and allied areas, this book will be an asset for researchers, faculty, advances students, and industry professionals in many fields.

This new volume, Cognitive Computing Systems: Applications and Technological Advancements, explores the emerging area of artificial intelligence that encompasses machine self-learning, human-computer interaction, natural language processing, data mining and more. It introduces cognitive computing systems, highlights their key applications, discusses the technologies used in cognitive systems, and explains underlying models and architectures.

Focusing on scientific work for real-world applications, each chapter presents the use of cognitive computing and machine learning in specific application areas. These include the use of speech recognition technology, application of neural networks in construction management, elevating competency in education, comprehensive health monitoring systems, predicting type 2 diabetes, applications for smart agricultural technology, human resource management, and more.

With chapters from knowledgeable researchers in the area of artificial intelligence, cognitive computing, and allied areas, this book will be an asset for researchers, faculty, advances students, and industry professionals in many fields.

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists.

Features:

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists.

Features:

This new volume explores a plethora of blockchain-based solutions for big data and IoT applications, looking at advances in real-world applications in several sectors, including higher education, cybersecurity, agriculture, business and management, healthcare and biomedical science, construction and project management, smart city development, and others. Chapters explore emerging technology to combat the ever-increasing threat of security to computer systems and offer new architectural solutions for problems encountered in data management and security. The chapters help to provide a high level of understanding of various blockchain algorithms along with the necessary tools and techniques. The novel architectural solutions in the deployment of blockchain presented here are the core of the book.

This new volume explores a plethora of blockchain-based solutions for big data and IoT applications, looking at advances in real-world applications in several sectors, including higher education, cybersecurity, agriculture, business and management, healthcare and biomedical science, construction and project management, smart city development, and others. Chapters explore emerging technology to combat the ever-increasing threat of security to computer systems and offer new architectural solutions for problems encountered in data management and security. The chapters help to provide a high level of understanding of various blockchain algorithms along with the necessary tools and techniques. The novel architectural solutions in the deployment of blockchain presented here are the core of the book.

Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines.

Features

• Covers the fundamentals, history, reality and challenges of cancer

• Presents concepts and analysis of different cancers in humans

• Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer

• Offers real-world examples of cancer prediction

• Reviews strategies and tools used in cancer prediction

• Explores the future prospects in cancer prediction and treatment

Readers will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions.

This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.

Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines.

Features

• Covers the fundamentals, history, reality and challenges of cancer

• Presents concepts and analysis of different cancers in humans

• Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer

• Offers real-world examples of cancer prediction

• Reviews strategies and tools used in cancer prediction

• Explores the future prospects in cancer prediction and treatment

Readers will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions.

This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.

The book intends to cover various problematic aspects of emerging smart computing and self-adapting technologies comprising of machine learning, artificial intelligence, deep learning, robotics, cloud computing, fog computing, data mining algorithms, including emerging intelligent and smart applications related to these research areas. Further coverage includes implementation of self-adaptation architecture for smart devices, self-adaptive models for smart cities and self-driven cars, decentralized self-adaptive computing at the edge networks, energy-aware AI-based systems, M2M networks, sensors, data analytics, algorithms and tools for engineering self-adaptive systems, and so forth.

Acts as guide to Self-healing and Self-adaptation based fully automatic future technologies Discusses about Smart Computational abilities and self-adaptive systems Illustrates tools and techniques for data management and explains the need to apply, and data integration for improving efficiency of big data Exclusive chapter on the future of self-stabilizing and self-adaptive systems of systems Covers fields such as automation, robotics, medical sciences, biomedical and agricultural sciences, healthcare and so forth

This book is aimed researchers and graduate students in machine learning, information technology, and artificial intelligence.

The book intends to cover various problematic aspects of emerging smart computing and self-adapting technologies comprising of machine learning, artificial intelligence, deep learning, robotics, cloud computing, fog computing, data mining algorithms, including emerging intelligent and smart applications related to these research areas. Further coverage includes implementation of self-adaptation architecture for smart devices, self-adaptive models for smart cities and self-driven cars, decentralized self-adaptive computing at the edge networks, energy-aware AI-based systems, M2M networks, sensors, data analytics, algorithms and tools for engineering self-adaptive systems, and so forth.

Acts as guide to Self-healing and Self-adaptation based fully automatic future technologies Discusses about Smart Computational abilities and self-adaptive systems Illustrates tools and techniques for data management and explains the need to apply, and data integration for improving efficiency of big data Exclusive chapter on the future of self-stabilizing and self-adaptive systems of systems Covers fields such as automation, robotics, medical sciences, biomedical and agricultural sciences, healthcare and so forth

This book is aimed researchers and graduate students in machine learning, information technology, and artificial intelligence.

In recent years, drones have been integrated with the Internet of Things to offer a variety of exciting new applications. Here is a detailed exploration of adapting and implementing Internet of Drones technologies in real-world applications, emphasizing solutions to architectural challenges and providing a clear overview of standardization and regulation, implementation plans, and privacy concerns. The book discusses the architectures and protocols for drone communications, implementing and deploying of 5G-drone setups, security issues, deep learning techniques applied on real-time footage, and more. It also explores some of the varied applications, such as for monitoring and analysis of troposphere pollutants, providing services and communications in smart cities (such as for weather forecasting, communications, transport, safety and protection), for disaster relief management, for agricultural crop monitoring, and more.

In recent years, drones have been integrated with the Internet of Things to offer a variety of exciting new applications. Here is a detailed exploration of adapting and implementing Internet of Drones technologies in real-world applications, emphasizing solutions to architectural challenges and providing a clear overview of standardization and regulation, implementation plans, and privacy concerns. The book discusses the architectures and protocols for drone communications, implementing and deploying of 5G-drone setups, security issues, deep learning techniques applied on real-time footage, and more. It also explores some of the varied applications, such as for monitoring and analysis of troposphere pollutants, providing services and communications in smart cities (such as for weather forecasting, communications, transport, safety and protection), for disaster relief management, for agricultural crop monitoring, and more.

SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems.

Features:

This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.

SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems.

Features:

This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.

This book explores opportunities and challenges in the field of Internet of Everything (IoE) security and privacy under the umbrella of distributed ledger technologies and blockchain technology including distributed consensus mechanisms, crypto-sensors, encryption algorithms, and fault tolerance mechanisms for devices and systems. It focusses on the applicability of blockchain technology, including architectures and platforms for blockchain and IoE, authentication and encryption algorithms for IoE, malicious transactions detection, blockchain for forensics, and so forth.

This book is aimed at researchers and graduate students in computing, cryptography, IoT, computer engineering, and networks.

This book explores opportunities and challenges in the field of Internet of Everything (IoE) security and privacy under the umbrella of distributed ledger technologies and blockchain technology including distributed consensus mechanisms, crypto-sensors, encryption algorithms, and fault tolerance mechanisms for devices and systems. It focusses on the applicability of blockchain technology, including architectures and platforms for blockchain and IoE, authentication and encryption algorithms for IoE, malicious transactions detection, blockchain for forensics, and so forth.

This book is aimed at researchers and graduate students in computing, cryptography, IoT, computer engineering, and networks.