Computationally Intensive Statistics For Intelligent Iot
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Computationally Intensive Statistics for Intelligent IoT by Debabrata Samanta,Amit Banerjee Pdf
The book covers computational statistics, its methodologies and applications for IoT device. It includes the details in the areas of computational arithmetic and its influence on computational statistics, numerical algorithms in statistical application software, basics of computer systems, statistical techniques, linear algebra and its role in optimization techniques, evolution of optimization techniques, optimal utilization of computer resources, and statistical graphics role in data analysis. It also explores computational inferencing and computer model's role in design of experiments, Bayesian analysis, survival analysis and data mining in computational statistics.
Computationally Intensive Statistics for Intelligent IoT by Debabrata Samanta,Amit Banerjee Pdf
The book covers computational statistics, its methodologies and applications for IoT device. It includes the details in the areas of computational arithmetic and its influence on computational statistics, numerical algorithms in statistical application software, basics of computer systems, statistical techniques, linear algebra and its role in optimization techniques, evolution of optimization techniques, optimal utilization of computer resources, and statistical graphics role in data analysis. It also explores computational inferencing and computer model's role in design of experiments, Bayesian analysis, survival analysis and data mining in computational statistics.
Computational and Statistical Methods in Intelligent Systems by Radek Silhavy,Petr Silhavy,Zdenka Prokopova Pdf
This book presents real-world problems and pioneering research in computational statistics, mathematical modeling, artificial intelligence and software engineering in the context of intelligent systems. It gathers the peer-reviewed proceedings of the 2nd Computational Methods in Systems and Software 2018 (CoMeSySo 2018), a conference that broke down traditional barriers by being held online. The goal of the event was to provide an international forum for discussing the latest high-quality research results.
Data Analytics, Computational Statistics, and Operations Research for Engineers by Debabrata Samanta,SK Hafizul Islam,Naveen Chilamkurti,Mohammad Hammoudeh Pdf
With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.
Data Intensive Industrial Asset Management by Farhad Balali,Jessie Nouri,Adel Nasiri,Tian Zhao Pdf
This book presents a step by step Asset Health Management Optimization Approach Using Internet of Things (IoT). The authors provide a comprehensive study which includes the descriptive, diagnostic, predictive, and prescriptive analysis in detail. The presentation focuses on the challenges of the parameter selection, statistical data analysis, predictive algorithms, big data storage and selection, data pattern recognition, machine learning techniques, asset failure distribution estimation, reliability and availability enhancement, condition based maintenance policy, failure detection, data driven optimization algorithm, and a multi-objective optimization approach, all of which can significantly enhance the reliability and availability of the system.
Printed Antennas by Praveen Kumar Malik,Arshi Naim,Ramendra Singh Pdf
This collection covers different printed microstrip antenna designs,from rectangular to circular, broadband, dual-band, and millimeter-wave microstrip antennas to microstrip arrays. It further presents a new analysis of the rectangular and circular microstrip antenna efficiency and surface wave phenomena. The book Covers the latest advances and applications of microstrip antennas Discusses methods and techniques used for the enhancement of the performance parameters of the microstrip antenna Presents low-power wide area network (LPWAN) proximity-coupled antenna for Internet of Things applications. Highlights a new analysis of rectangular and circular microstrip antenna efficiency and surface wave phenomena. Showcases implantable antennas, H-shaped antennas, and wideband implantable antennas for biomedical applications Printed Antennas discusses the latest advances such as the Internet of Things for antenna applications, device-to-device communication, satellite communication, and wearable textile antenna in the field of communication. It further presents methods and techniques used for the enhancement of the performance parameters of the microstrip antenna and covers the design of conformal and miniaturized antenna structures for various applications. It will serve as an ideal reference text for senior undergraduates, graduate students, and researchers in fields including electrical engineering, electronics and communications engineering, and computer engineering.
Innovations in Computational Intelligence, Big Data Analytics and Internet of Things by Sam Goundar,J. Avanija,Gurram Sunitha,K. Reddy Madhavi Pdf
As sensors spread across almost every industry, the internet of things is going to trigger a massive influx of big data. We delve into where IoT will have the biggest impact and what it means for the future of big data analytics. Internet of Things is changing the face of different sectors such as manufacturing, health-care, business, education etc. by completely redefining the way people, devices, and apps connect and interact with each other in the eco system. From personal fitness and wellness sensors, implantable devices to surgical robots – IoT is bringing in new tools and efficiencies in the ecosystem resulting in more integrated healthcare. Application of computational intelligence techniques is today considered as a key success factor to solve the growing scale and complexity of problems in the field of health care systems, agriculture, e-commerce etc. The convergence of Computational intelligence, Big Data and IoT provides new opportunities and revolutionize business in huge way. This book will support industry and governmental agencies to facilitate and make sense of myriad connected devices in coming decade. This book offers the recent advancements in Computational Intelligence, IoT and Big Data Analytics. • Development of models and algorithms for employing IoT based facilities in healthcare, industry, agriculture, e- commerce, manufacturing, business etc. • Methods for collection, management retrieval and processing of Big Data in various domains. • Provides taxonomy of challenges, issues and research directions in applications of computational intelligence techniques in different domains
Computational Intelligence in the Internet of Things by Purnomo, Hindriyanto Dwi Pdf
In recent years, the need for smart equipment has increased exponentially with the upsurge in technological advances. To work to their fullest capacity, these devices need to be able to communicate with other devices in their network to exchange information and receive instructions. Computational Intelligence in the Internet of Things is an essential reference source that provides relevant theoretical frameworks and the latest empirical research findings in the area of computational intelligence and the Internet of Things. Featuring research on topics such as data analytics, machine learning, and neural networks, this book is ideally designed for IT specialists, managers, professionals, researchers, and academicians.
Edge Computational Intelligence for AI-Enabled IoT Systems by Shrikaant Kulkarni,Jaiprakash Dwivedi,Dinda Pramanta,Yuichiro Tanaka Pdf
Edge computational intelligence is an interface between edge computing and artificial intelligence (AI) technologies. This interfacing represents a paradigm shift in the world of work by enabling a broad application areas and customer-friendly solutions. Edge computational intelligence technologies are just in their infancy. Edge Computational Intelligence for AI-Enabled IoT Systems looks at the trends and advances in edge computing and edge AI, the services rendered by them, related security and privacy issues, training algorithms, architectures, and sustainable AI-enabled IoT systems. Together, these technologies benefit from ultra-low latency, faster response times, lower bandwidth costs and resilience from network failure, and the book explains the advantages of systems and applications using intelligent IoT devices that are at the edge of a network and close to users. It explains how to make most of edge and cloud computing as complementary technologies or used in isolation for extensive and widespread applications. The advancement in IoT devices, networking facilities, parallel computation and 5G, and robust infrastructure for generalized machine learning have made it possible to employ edge computational intelligence in diverse areas and in diverse ways. The book begins with chapters that cover Edge AI services on offer as compared to conventional systems. These are followed by chapters that discuss security and privacy issues encountered during the implementation and execution of edge AI and computing services The book concludes with chapters looking at applications spread across different areas of edge AI and edge computing and also at the role of computational intelligence in AI-driven IoT systems.
Advances in Applications of Computational Intelligence and the Internet of Things by Rajdeep Chowdhury,S. K. Niranjan Pdf
This new volume illustrates the diverse applications of IoT. The volume addresses the crucial issue of data safekeeping along with the development of a new cryptographic and security technology as well as a range of other advances in IoT. The volume looks at the application of IoT in medical technology and healthcare, including the design of IoT-based mobile healthcare units and a blockchain technique based smart health record system. Other topics include a blended IoT-enabled learning approach through a study employing clustering techniques, an IoT-enabled garbage disposal system with an advanced message notification system through an android application, IoT-based self-healing concrete that uses bacteria and environmental waste, an IoT-enabled trash-the-ash application that regulates flow, and more. The fresh and innovative advances that demonstrate computational intelligence and IoT in practice that are discussed in this volume will be informative for academicians, scholars, scientists, industry professionals, policymakers, government and non-government organizations, and others.
Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications by Deepak Gupta,Aditya Khamparia Pdf
A practical guide to the design, implementation, evaluation, and deployment of emerging technologies for intelligent IoT applications With the rapid development in artificially intelligent and hybrid technologies, IoT, edge, fog-driven, and pervasive computing techniques are becoming important parts of our daily lives. This book focuses on recent advances, roles, and benefits of these technologies, describing the latest intelligent systems from a practical point of view. Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications is also valuable for engineers and professionals trying to solve practical, economic, or technical problems. With a uniquely practical approach spanning multiple fields of interest, contributors cover theory, applications, and design methodologies for intelligent systems. These technologies are rapidly transforming engineering, industry, and agriculture by enabling real-time processing of data via computational, resource-oriented metaheuristics and machine learning algorithms. As edge/fog computing and associated technologies are implemented far and wide, we are now able to solve previously intractable problems. With chapters contributed by experts in the field, this book: Describes Machine Learning frameworks and algorithms for edge, fog, and pervasive computing Considers probabilistic storage systems and proven optimization techniques for intelligent IoT Covers 5G edge network slicing and virtual network systems that utilize new networking capacity Explores resource provisioning and bandwidth allocation for edge, fog, and pervasive mobile applications Presents emerging applications of intelligent IoT, including smart farming, factory automation, marketing automation, medical diagnosis, and more Researchers, graduate students, and practitioners working in the intelligent systems domain will appreciate this book’s practical orientation and comprehensive coverage. Intelligent IoT is revolutionizing every industry and field today, and Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications provides the background, orientation, and inspiration needed to begin.
Machine Learning and IoT for Intelligent Systems and Smart Applications by Madhumathy P,M Vinoth Kumar,R. Umamaheswari Pdf
The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects. Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT. This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.
Computational Statistical Methodologies and Modeling for Artificial Intelligence by Priyanka Harjule,Azizur Rahman,Basant Agarwal,Vinita Tiwari Pdf
This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence
Shaping the Future of IoT with Edge Intelligence by Rute C. Sofia,John Soldatos Pdf
This book presents the technologies that empower edge intelligence, along with their use in novel IoT solutions. Specifically, it presents how 5G/6G, Edge AI, and Blockchain solutions enable novel IoT-based decentralized intelligence use cases at the edge of the cloud/edge/IoT continuum. Emphasis is placed on presenting how these technologies support a wide array of functional and non-functional requirements spanning latency, performance, cybersecurity, data protection, real-time performance, energy efficiency, and more. The various chapters of the book are contributed by several EU-funded projects, which have recently developed novel IoT platforms that enable the development and deployment of edge intelligence applications based on the cloud/edge paradigm. Each one of the projects employs its own approach and uses a different mix of networking, middleware, and IoT technologies. Therefore, each of the chapters of the book contributes a unique perspective on the capabilities of enabling technologies and their integration in practical real-life applications in different sectors. The book is structured in five distinct parts. Each one of the first four parts focuses on a specific set of enabling technologies for edge intelligence and smart IoT applications in the cloud/edge/IoT continuum. Furthermore, the fifth part provides information about complementary aspects of next-generation IoT technology, including information about business models and IoT skills. Specifically: The first part focuses on 5G/6G networking technologies and their roles in implementing edge intelligence applications. The second part presents IoT applications that employ machine learning and other forms of Artificial Intelligence at the edge of the network. The third part illustrates decentralized IoT applications based on distributed ledger technologies. The fourth part is devoted to the presentation of novel IoT applications and use cases spanning the cloud/edge/IoT continuum. The fifth part discusses complementary aspects of IoT technologies, including business models and digital skills.
