Korhan Cengiz – författare

This book focuses on RFID (Radio Frequency Identification), IoT (Internet of Things), and WSN (Wireless Sensor Network). It includes contributions that discuss the security and privacy issues as well as the opportunities and applications that are tightly linked to sensitive infrastructures and strategic services. This book addresses the complete functional framework and workflow in IoT-enabled RFID systems and explores basic and high-level concepts. It is based on the latest technologies and covers the major challenges, issues, and advances in the field. It presents data acquisition and case studies related to data-intensive technologies in RFID-based IoT and includes WSN-based systems and their security.It can serve as a manual for those in the industry while also helping beginners to understand both the basic and advanced aspects of IoT-based RFID-related issues. This book can be a premier interdisciplinary platform for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered, and find solutions that have been adopted in the fields of IoT and analytics.

This book focuses on RFID (Radio Frequency Identification), IoT (Internet of Things), and WSN (Wireless Sensor Network). It includes contributions that discuss the security and privacy issues as well as the opportunities and applications that are tightly linked to sensitive infrastructures and strategic services. This book addresses the complete functional framework and workflow in IoT-enabled RFID systems and explores basic and high-level concepts. It is based on the latest technologies and covers the major challenges, issues, and advances in the field. It presents data acquisition and case studies related to data-intensive technologies in RFID-based IoT and includes WSN-based systems and their security.It can serve as a manual for those in the industry while also helping beginners to understand both the basic and advanced aspects of IoT-based RFID-related issues. This book can be a premier interdisciplinary platform for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered, and find solutions that have been adopted in the fields of IoT and analytics.

Metaverse Technologies in Healthcare focuses on data analysis, utilizing the possibilities of data to increase the effectiveness of healthcare organizations. As healthcare services aim to maintain the physical, mental, social and emotional well-being of human lives while the Metaverse is a blend of technological trends- Artificial Intelligence (AI), Augmented Reality (AR) and Virtual Reality (VR), collectively, they can deliver treatments and medicines, lower costs, and substantially enhance patient outcomes. The book redefines the digital health experience and describes the advantages of the Metaverse-based NFT technology in the healthcare sector, facilitating NFT avatars to interact with targeted audiences, and more.

Shows the potential of digital experiences on the healthcare sectorFocuses on the leading channels fueling the digital health space, such as Telemedicine, Digital Twins, Block chain, Internet of Things, and Robotics, providing new directions in this sectorProvides guidance to healthcare companies on how to augment their Digital Roadmaps with personalized care

Intelligent Semantic Analysis for Healthcare explores the latest trends, developments, and future directions of intelligent semantic analysis techniques on retrieving and managing meaningful medical information for healthcare information systems. The book explores different computational methods, ideas, strategies, and techniques to analyze relevant healthcare information in an innovative and efficient way, thus bridging the gap between gathering and comprehending data with healthcare and biological applications. It offers a comprehensive view of intelligent semantic analysis in healthcare, bridging the gap between data collection and healthcare applications, and providing innovative computational methods for data analysis.Sections focus on intelligent semantic analysis rather than broader topics of big data and healthcare analytics. Additionally, the book is geared towards practical approaches and innovative techniques for state-of-the-art and current challenges in healthcare data management.Explores the operation of future healthcare data systems, enhancing clinical resources to ensure optimal patient outcomesHighlights trends, challenges, opportunities, and future areas in healthcare informatics, focusing on accessing extensive datasets containing potentially lifesaving informationPresents case studies that demonstrate the intelligent analysis of healthcare information through the combination of real-time data, predictions, and advanced computer programs

Explainable AI in Clinical Practice: Methods, Applications, and Implementation bridges the gap between artificial intelligence capabilities and their practical implementation in healthcare. The book explores applications of explainable AI in diagnostic support and treatment planning, offering insights into making AI systems interpretable and accountable. Through real-world case studies and ethical frameworks, readers learn to transform opaque AI systems into tools that enhance clinical practice while maintaining high patient care standards. This volume unites leading experts to provide a comprehensive framework for implementing explainable AI, ensuring that AI-driven decisions are transparent, trustworthy, and clinically sound. Targeted solutions in the book cater to diverse stakeholders in the healthcare AI ecosystem. Healthcare professionals will gain confidence in integrating AI tools, while technical teams will receive implementation guidelines. This book is essential for anyone seeking to responsibly and effectively navigate the complexities of AI in healthcare.Provides a comprehensive framework for implementing explainable AI in healthcare, ensuring that AI-driven decisions are transparent, trustworthy, and clinically soundIncludes real-world case studies that illustrate practical applications of explainable AIOffers targeted solutions for diverse stakeholders in the healthcare AI ecosystem

Explainable AI in Clinical Practice: Advanced Applications and Future Directions builds on foundational concepts to explore the practical implementation and emerging trends of transparent AI in healthcare. Featuring contributions from leading experts, this volume presents advanced methodologies, real-world case studies across various medical specialties, and strategies for overcoming ethical, regulatory, and operational challenges. The book offers comprehensive frameworks for integrating explainable AI into clinical workflows, emphasizing trust, patient understanding, and regulatory compliance. In addition, it examines future technologies such as federated learning, multimodal systems, and human-AI collaboration, providing insights into the evolving landscape of AI in medicine.Essential for healthcare professionals, researchers, and policymakers, this volume aims to accelerate the responsible adoption of explainable AI, ultimately enhancing patient care, clinical decision-making, and healthcare system efficiency.Provides comprehensive implementation frameworks that guide the deployment of explainable AI in healthcare, addressing technical, organizational, ethical, and regulatory challengesPresents detailed, specialty-specific case studies that demonstrate successful real-world applications of explainable AI across various clinical disciplinesExplores future directions and emerging technologies, offering insights into how explainable AI will integrate with innovations like federated learning and multimodal systems to shape healthcare’s evolution

This book is written in a clear and thorough way to cover both the traditional and modern uses of artificial intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model.Features:A detailed description of basic intelligent techniques (fuzzy logic, genetic algorithm and neural network using MATLAB)A detailed description of the hybrid intelligent technique called the adaptive fuzzy inference technique (ANFIS)Formulation of the nonlinear model like analysis of ANOVA and response surface methodologyVariety of solved problems on ANOVA and RSMCase studies of above mentioned intelligent techniques on the different process control systemsThis book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.

This book presents soft computing techniques and applications used in healthcare systems, along with the latest advancements. Written as a guide for assessing the roles that these techniques play, the book also highlights implementation strategies, lists problem-solving solutions, and paves the way for future research endeavors in smart and next-generation healthcare systems.This book provides applications of soft computing techniques related to healthcare systems and can be used as a reference guide for assessing the roles that various techniques, such as machine learning, fuzzy logic, and statical mathematics, play in the advancements of smart healthcare systems. The book presents the basics as well as the advanced concepts to help beginners, as well as industry professionals, get up to speed on the latest developments in healthcare systems. The book examines descriptive, predictive, and social network techniques and discusses analytical tools and the important role they play in finding solutions to problems in healthcare systems. A framework of robust and novel healthcare techniques is highlighted, as well as implementation strategies and a setup for future research endeavors.Healthcare Systems Using Soft Computing Techniques is a valuable resource for researchers and postgraduate students in healthcare systems engineering, computer science, information technology, and applied mathematics. The book introduces beginners to—and at the same time brings industry professionals up to speed with—the important role soft computing techniques play in smart healthcare systems.

This book presents soft computing techniques and applications used in healthcare systems, along with the latest advancements. Written as a guide for assessing the roles that these techniques play, the book also highlights implementation strategies, lists problem-solving solutions, and paves the way for future research endeavors in smart and next-generation healthcare systems.This book provides applications of soft computing techniques related to healthcare systems and can be used as a reference guide for assessing the roles that various techniques, such as machine learning, fuzzy logic, and statical mathematics, play in the advancements of smart healthcare systems. The book presents the basics as well as the advanced concepts to help beginners, as well as industry professionals, get up to speed on the latest developments in healthcare systems. The book examines descriptive, predictive, and social network techniques and discusses analytical tools and the important role they play in finding solutions to problems in healthcare systems. A framework of robust and novel healthcare techniques is highlighted, as well as implementation strategies and a setup for future research endeavors.Healthcare Systems Using Soft Computing Techniques is a valuable resource for researchers and postgraduate students in healthcare systems engineering, computer science, information technology, and applied mathematics. The book introduces beginners to—and at the same time brings industry professionals up to speed with—the important role soft computing techniques play in smart healthcare systems.

The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations.Key sailing Features: The impact of the proposed book is to provide a major area of concern to develop a foundation for the implementation process of new image processing and IoT devices based on Energy, Industry, and Healthcare related technology. The researchers working on image processing and IoT devices can correlate their work with other requirements of advanced technology in Energy, Industry, and Healthcare domain. To make aware of the latest technology like AI and Machine learning in Energy, Industry, and Healthcare related technology. Useful for the researcher to explore new things like Security, cryptography, and privacy in Energy, Industry, and Healthcare related technology. People who want to start in Energy, Industry, and Healthcare related technology with image processing and IoT world.

The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations.Key sailing Features: The impact of the proposed book is to provide a major area of concern to develop a foundation for the implementation process of new image processing and IoT devices based on Energy, Industry, and Healthcare related technology. The researchers working on image processing and IoT devices can correlate their work with other requirements of advanced technology in Energy, Industry, and Healthcare domain. To make aware of the latest technology like AI and Machine learning in Energy, Industry, and Healthcare related technology. Useful for the researcher to explore new things like Security, cryptography, and privacy in Energy, Industry, and Healthcare related technology. People who want to start in Energy, Industry, and Healthcare related technology with image processing and IoT world.

This text discusses problems and needs with the implementation of a 5G mobile communications system in the healthcare sector. It covers the issues related to advanced modulation schemes, telehealth, and remote diagnosis. It discusses important topics including virtual healthcare monitoring, spectrum sensing techniques, the role of 5G in medical applications, the role of nano- communication in healthcare informatics, and remote diagnosis. The text will be useful for graduate students, academic researchers, and professionals in the fields of electrical, and electronics and communication engineering, and allied healthcare.This book:Discusses novel architecture to manage the allocation of resources, and the interference issue among existing and advanced radiosProvides focus to estimate the performance, cost and accommodation of the next generation technology design for the IoT, modern health- care, and educationCovers advanced technologies and their role in healthcareDiscusses key topics including spectrum access, advanced waveforms, which can help in standardization of 5G based smart hospitalExplores the impact of telemedicine in smart healthcareThis reference text covers the latest advances in the field of 5G mobile communication for healthcare informatics, addressing both original algorithm development and new applications of 5G mobile Communications.

This text discusses problems and needs with the implementation of a 5G mobile communications system in the healthcare sector. It covers the issues related to advanced modulation schemes, telehealth, and remote diagnosis. It discusses important topics including virtual healthcare monitoring, spectrum sensing techniques, the role of 5G in medical applications, the role of nano- communication in healthcare informatics, and remote diagnosis. The text will be useful for graduate students, academic researchers, and professionals in the fields of electrical, and electronics and communication engineering, and allied healthcare.This book:Discusses novel architecture to manage the allocation of resources, and the interference issue among existing and advanced radiosProvides focus to estimate the performance, cost and accommodation of the next generation technology design for the IoT, modern health- care, and educationCovers advanced technologies and their role in healthcareDiscusses key topics including spectrum access, advanced waveforms, which can help in standardization of 5G based smart hospitalExplores the impact of telemedicine in smart healthcareThis reference text covers the latest advances in the field of 5G mobile communication for healthcare informatics, addressing both original algorithm development and new applications of 5G mobile Communications.

This book is written in a clear and thorough way to cover both the traditional and modern uses of artificial intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model.Features:A detailed description of basic intelligent techniques (fuzzy logic, genetic algorithm and neural network using MATLAB)A detailed description of the hybrid intelligent technique called the adaptive fuzzy inference technique (ANFIS)Formulation of the nonlinear model like analysis of ANOVA and response surface methodologyVariety of solved problems on ANOVA and RSMCase studies of above mentioned intelligent techniques on the different process control systemsThis book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.

This book provides a comprehensive study of healthcare system engineering (HCSE), which uses engineering analysis and design concepts to improve healthcare services. It further discusses ethical and legal considerations in the global healthcare industry, the use of virtual and augmented reality in healthcare surgery, and smart healthcare systems for elderly people using Industry 4.0.This book:Showcases the efficient use of financial, human, technical, and organizational resources for the enhancement of the performance and quality of healthcare processes. Discusses advanced techniques, input-collecting mechanisms, and features utilized for human behavior analysis applications in various domains. Reviews advances in computation, communication, and device technologies for analyzing information on human function and disability. Presents artificial intelligence and machine learning-based computation techniques in healthcare systems and biomedical engineering management. Explains the use of virtual and augmented reality in healthcare surgery and robotic process automationin themedical field. It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, and biomedical engineering.

Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.

The book provides an essential overview of AI techniques in disease management and how these computational methods can lead to further innovations in healthcare. Design and Forecasting Models for Disease Management is a resourceful volume of 13 chapters that elaborates on computational methods and how AI techniques can aid in smart disease management. It contains several statistical and AI techniques that can be used to acquire data on many different diseases. The main objective of this book is to demonstrate how AI techniques work for early disease detection and forecasting useful information for medical experts. As such, this volume intends to serve as a resource to elicit and elaborate on possible intelligent mechanisms for helping detect early signs of diseases. Additionally, the book examines numerous machine learning and data analysis techniques in the biomedical field that are used for detecting and forecasting disease management at the cellular level. It discusses various applications of image segmentation, data analysis techniques, and hybrid machine learning techniques for illnesses, and encompasses modeling, prediction, and diagnosis of disease data. Audience Researchers, engineers and graduate students in the fields of computational biology, information technology, bioinformatics, and epidemiology.

The book analyzes the combination of intelligent data analytics with the intricacies of biological data that has become a crucial factor for innovation and growth in the fast-changing field of bioinformatics and biomedical systems. Intelligent Data Analytics for Bioinformatics and Biomedical Systems delves into the transformative nature of data analytics for bioinformatics and biomedical research. It offers a thorough examination of advanced techniques, methodologies, and applications that utilize intelligence to improve results in the healthcare sector. With the exponential growth of data in these domains, the book explores how computational intelligence and advanced analytic techniques can be harnessed to extract insights, drive informed decisions, and unlock hidden patterns from vast datasets. From genomic analysis to disease diagnostics and personalized medicine, the book aims to showcase intelligent approaches that enable researchers, clinicians, and data scientists to unravel complex biological processes and make significant strides in understanding human health and diseases. This book is divided into three sections, each focusing on computational intelligence and data sets in biomedical systems. The first section discusses the fundamental concepts of computational intelligence and big data in the context of bioinformatics. This section emphasizes data mining, pattern recognition, and knowledge discovery for bioinformatics applications. The second part talks about computational intelligence and big data in biomedical systems. Based on how these advanced techniques are utilized in the system, this section discusses how personalized medicine and precision healthcare enable treatment based on individual data and genetic profiles. The last section investigates the challenges and future directions of computational intelligence and big data in bioinformatics and biomedical systems. This section concludes with discussions on the potential impact of computational intelligence on addressing global healthcare challenges. Audience Intelligent Data Analytics for Bioinformatics and Biomedical Systems is primarily targeted to professionals and researchers in bioinformatics, genetics, molecular biology, biomedical engineering, and healthcare. The book will also suit academicians, students, and professionals working in pharmaceuticals and interpreting biomedical data.

The main goal of Smart Agritech: Robotics, AI, and Internet of Things (IoT) in Agriculture is to explore how emerging technologies such as robotics, artificial intelligence (AI), and IoT can be leveraged to improve efficiency, sustainability, and productivity in agriculture. Agriculture has always been a vital sector of the global economy, providing food and raw materials for industries and households. However, with the growing population, changing climate conditions, and limited resources, the agriculture sector faces numerous challenges. To address these challenges, farmers and agricultural companies are turning to advanced technologies such as Robotics, Artificial Intelligence (AI), and the Internet of Things (IoT). This exciting new volume provides a comprehensive overview of the latest technological advances in agriculture, focusing on these three cutting-edge technologies. The book will explore the potential benefits of these technologies in improving agricultural efficiency, productivity, and sustainability. Whether for the veteran engineer, scientist in the lab, student, or faculty, this groundbreaking new volume is a valuable resource for researchers and other industry professionals interested in the intersection of technology and agriculture.

This volume introduces the key evolving applications of IoT in the medical field for patient care delivery through the usage of smart devices. It shows how IoT opens the door to a wealth of relevant healthcare information through real-time data analysis as well as testing, providing reliable and pragmatic data that yields enhanced solutions and discovery of previously undiscovered issues.This new volume discusses IoT devices that are deployed for enabling patient health tracking, various emergency issues, smart administration of patients, etc. It looks at the problems of cardiac analysis in e-healthcare, explores the employment of smart devices aimed for different patient issues, and examines the usage of Arduino kits where the data can be transferred to the cloud for internet-based uses. The volume also considers the roles of IoT in electroencephalography (EEG) and magnetic resonance imaging (MRI), which play significant roles in biomedical applications. This book also incorporates the use of IoT applications for smart wheelchairs, telemedicine, GPS positioning of heart patients, smart administration with drug tracking, and more.

This volume introduces the key evolving applications of IoT in the medical field for patient care delivery through the usage of smart devices. It shows how IoT opens the door to a wealth of relevant healthcare information through real-time data analysis as well as testing, providing reliable and pragmatic data that yields enhanced solutions and discovery of previously undiscovered issues.This new volume discusses IoT devices that are deployed for enabling patient health tracking, various emergency issues, smart administration of patients, etc. It looks at the problems of cardiac analysis in e-healthcare, explores the employment of smart devices aimed for different patient issues, and examines the usage of Arduino kits where the data can be transferred to the cloud for internet-based uses. The volume also considers the roles of IoT in electroencephalography (EEG) and magnetic resonance imaging (MRI), which play significant roles in biomedical applications. This book also incorporates the use of IoT applications for smart wheelchairs, telemedicine, GPS positioning of heart patients, smart administration with drug tracking, and more.

As enterprise access networks evolve with a larger number of mobile users, a wide range of devices and new cloud-based applications, managing user performance on an end-to-end basis has become rather challenging. Recent advances in big data network analytics combined with AI and cloud computing are being leveraged to tackle this growing problem. AI is becoming further integrated with software that manage networks, storage, and can compute.This edited book focuses on how new network analytics, IoTs and Cloud Computing platforms are being used to ingest, analyse and correlate a myriad of big data across the entire network stack in order to increase quality of service and quality of experience (QoS/QoE) and to improve network performance. From big data and AI analytical techniques for handling the huge amount of data generated by IoT devices, the authors cover cloud storage optimization, the design of next generation access protocols and internet architecture, fault tolerance and reliability in intelligent networks, and discuss a range of emerging applications.This book will be useful to researchers, scientists, engineers, professionals, advanced students and faculty members in ICTs, data science, networking, AI, machine learning and sensing. It will also be of interest to professionals in data science, AI, cloud and IoT start-up companies, as well as developers and designers.

This book aims at offering a unique collection of ideas and experiences mainly focusing on the main streams and merger of Artificial Intelligence (AI) and the Internet of Things (IoT) for a wide slice of the communication and networking community.

This book aims at offering a unique collection of ideas and experiences mainly focusing on the main streams and merger of Artificial Intelligence (AI) and the Internet of Things (IoT) for a wide slice of the communication and networking community.

By adopting these innovations, farmers can produce more with fewer resources, ensuring food security while preserving the environment.Embracing technology-driven agriculture is crucial for meeting global food demands sustainably, combating climate change, and fostering economic resilience in farming communities.

Energy is a key source of economic growth due to its involvement as the primary input. Energy drives economic productivity and industrial growth. It can be considered as the prime requirement for the modern economy. Solar energy is a renewable source of energy that can be used to produce heat or generate electricity. The total amount of solar energy available on Earth’s surface is vastly in excess of the world’s current and anticipated energy requirements. In the 21st century, solar energy is expected to become increasingly attractive as a renewable energy source. An increase in the share of solar energy may destabilize the grid. To overcome the issues of grid instability, specifically in remote areas, BIM and GIS-based microgrid planning based on data can be effectively used. BIM and GIS are used to assess alternative solutions and big data analytics in building solar electrical systems according to planning requirements and managing assets. The integration of BIM and GIS information systems for microgrid planning is appealing due to its potential benefits, such as it decreases the microgrid planning time and cost.The present book is about the advancements in technology for harnessing solar energy and the challenges associated with different modes of utilizing this inexhaustible renewable energy source. This book will be helpful for researchers, academicians, technologists, innovators, and industry experts working in the area of solar energy, artificial intelligence, and smart grids.