Abhishek Verma – författare

There is presently a drastic growth in multimedia data. During the Covid-19 pandemic, we observed that images helped doctors immensely in the rapid detection of Covid-19 infection in patients. There are many critical applications in which images play a vital role. These applications use raw image data to extract some useful information about the world around us. The quick extraction of valuable information from raw images is one challenge that academicians and professionals face in the present day. This is where image processing comes into action. Image processing’s primary purpose is to get an enhanced image or extract some useful information from raw image data. Therefore, there is a major need for some technique or system that addresses this challenge. Intelligent Systems have emerged as a solution to address quick image information extraction. In simple words, an Intelligent System can be defined as a mathematical model that adapts itself to deal with a problem’s dynamicity. These systems learn how to act so an image can reach an objective. An Intelligent System helps accomplish various image-processing functions like enhancement, segmentation, reconstruction, object detection, and morphing. The advent of Intelligent Systems in the image-processing field has leveraged many critical applications for humankind. These critical applications include factory automation, biomedical imaging analysis, decision econometrics, as well as related challenges.

There is presently a drastic growth in multimedia data. During the Covid-19 pandemic, we observed that images helped doctors immensely in the rapid detection of Covid-19 infection in patients. There are many critical applications in which images play a vital role. These applications use raw image data to extract some useful information about the world around us. The quick extraction of valuable information from raw images is one challenge that academicians and professionals face in the present day. This is where image processing comes into action. Image processing’s primary purpose is to get an enhanced image or extract some useful information from raw image data. Therefore, there is a major need for some technique or system that addresses this challenge. Intelligent Systems have emerged as a solution to address quick image information extraction. In simple words, an Intelligent System can be defined as a mathematical model that adapts itself to deal with a problem’s dynamicity. These systems learn how to act so an image can reach an objective. An Intelligent System helps accomplish various image-processing functions like enhancement, segmentation, reconstruction, object detection, and morphing. The advent of Intelligent Systems in the image-processing field has leveraged many critical applications for humankind. These critical applications include factory automation, biomedical imaging analysis, decision econometrics, as well as related challenges.

We live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyber security. We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements. However, they are undergoing rapid changes and need special attention. The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges. Therefore, there is a significant need to develop improved network management and cyber security solutions. To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges. More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.

We live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyber security. We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements. However, they are undergoing rapid changes and need special attention. The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges. Therefore, there is a significant need to develop improved network management and cyber security solutions. To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges. More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.

The advancements in intelligent decision-making techniques have elevated the efficiency of manufacturing industries and led to the start of the Industry 4.0 era. Industry 4.0 is revolutionizing the way companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and artificial intelligence and machine learning, into their production facilities throughout their operations. In the past few years, intelligent analytics has emerged as a solution that examines both historical and real-time data to uncover performance insights. Because the amount of data that needs analysis is growing daily, advanced technologies are necessary to collect, arrange, and analyze incoming data. This approach enables businesses to detect valuable connections and trends and make decisions that boost overall performance. In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive subdomains. To this end, the book will aim to review and highlight the challenges faced by intelligent analytics in Industry 4.0 and present the recent developments done to address those challenges.

The advancements in intelligent decision-making techniques have elevated the efficiency of manufacturing industries and led to the start of the Industry 4.0 era. Industry 4.0 is revolutionizing the way companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and artificial intelligence and machine learning, into their production facilities throughout their operations. In the past few years, intelligent analytics has emerged as a solution that examines both historical and real-time data to uncover performance insights. Because the amount of data that needs analysis is growing daily, advanced technologies are necessary to collect, arrange, and analyze incoming data. This approach enables businesses to detect valuable connections and trends and make decisions that boost overall performance. In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive subdomains. To this end, the book will aim to review and highlight the challenges faced by intelligent analytics in Industry 4.0 and present the recent developments done to address those challenges.

This book is an introduction to fundamental techniques of image analysis with machine vision and their applicability in Industry 5.0. It provides basic and emerging techniques in the field of image analysis and machine vision in Industry 5.0. It also covers an extensive study of recent related work and research challenges in the field. Further, it discusses some effective solutions to address the challenges of digitally transforming industrial activities and improving their efficiency. Provides effective and robust machine vision-enabled methods across different industrial fields, emphasizing their applicability and reliability Covers the emerging concepts of image analysis and machine vision utilized in the digital transformation of manufacturing activities under Industry 5.0 Discusses conceptual methodologies of image analysis and machine vision tailored for various industrial applications, providing insights into their practical implementation Practical issues on implementing machine vision applications with image analysis techniques in Industry 5.0 are addressed, offering guidance on method implementation Includes case studies of various industrial processes, highlighting current challenges and presenting effective solutions, offering real-world insights into the application of machine visionIt is a reference book for research students, scientists, and professionals working in the fields of image processing, computer vision, and the Internet of Things.

This book is a collection of the high-quality research articles presented at the International Conference on Business Intelligence and Data Analytics (BIDA 2025), organized by RV Institute of Management (RVIM), Bengaluru, India, during April 2025. This book covers state-of-the-art research articles from the researchers and practitioners working in the field of business intelligence, data analytics, decision support systems, data warehousing and data mining, big data analytics, predictive and prescriptive analytics, and machine learning for business applications and their real-world applications.

This book is a collection of the high-quality research articles presented at the International Conference on Business Intelligence and Data Analytics (BIDA 2025), organized by RV Institute of Management (RVIM), Bengaluru, India, during April 2025. The book covers state-of-the-art research articles from the researchers and practitioners working in the field of business intelligence, data analytics, decision support systems, data warehousing and data mining, big data analytics, predictive and prescriptive analytics, and machine learning for business applications and their real-world applications.

The purpose of this workshop is to spread the vast amount of information available on semiconductor physics to every possible field throughout the scientific community. As a result, the latest findings, research and discoveries can be quickly disseminated. This workshop provides all participating research groups with an excellent platform for interaction and collaboration with other members of their respective scientific community.This workshop’s technical sessions include various current and significant topics for applications and scientific developments, including •  Optoelectronics•  VLSI & ULSI Technology •  Photovoltaics •  MEMS & Sensors •  Device Modeling and Simulation •  High Frequency/ Power Devices •  Nanotechnology and Emerging Areas •  Organic Electronics •  Displays and LightingMany eminent scientists from various national and international organizations are actively participating with their latest research works and also equally supporting this mega event by joining the various organizing committees.

This book presents the proceedings of the International Conference on Recent Trends in Materials and Devices, which was conceived as a major contribution to large-scale efforts to foster Indian research and development in the field in close collaboration with the community of non-resident Indian researchers from all over the world. The research articles collected in this volume - selected from among the submissions for their intrinsic quality and originality, as well as for their potential value for further collaborations - document and report on a wide range of recent and significant results for various applications and scientific developments in the areas of Materials and Devices. The technical sessions covered include photovoltaics and energy storage, semiconductor materials and devices, sensors, smart and polymeric materials, optoelectronics, nanotechnology and nanomaterials, MEMS and NEMS, as well as emerging technologies.

This book presents the proceedings of the International Conference on Recent Trends in Materials and Devices, which was conceived as a major contribution to large-scale efforts to foster Indian research and development in the field in close collaboration with the community of non-resident Indian researchers from all over the world. The research articles collected in this volume - selected from among the submissions for their intrinsic quality and originality, as well as for their potential value for further collaborations - document and report on a wide range of recent and significant results for various applications and scientific developments in the areas of Materials and Devices. The technical sessions covered include photovoltaics and energy storage, semiconductor materials and devices, sensors, smart and polymeric materials, optoelectronics, nanotechnology and nanomaterials, MEMS and NEMS, as well as emerging technologies.

This book contains selected and peer-reviewed papers presented at the International Conference on Efficient Solar Power Generation and Energy Harvesting (ESPGEH 2019). The primary focus of the book is on latest advances and scientific developments in the field of solar energy. The book covers various topics such as solar photovoltaics, solar energy harvesting, smart materials for energy applications, hybrid renewable energy plant, and on-grid and off-grid power plant. The book also discusses current techniques to produce energy-efficient solar cells, emerging materials and processes to develop cost-effective solar cells, and different issues in energy management. Given the scope of the contents, this book will be of interest for researchers, professionals as well as policy makers.

This book contains selected and peer-reviewed papers presented at the International Conference on Efficient Solar Power Generation and Energy Harvesting (ESPGEH 2019).

This book presents the proceedings of the International Conference on Recent Trends in Materials and Devices (ICRTMD 2019) held in India. The conference provides a platform to tackle complex problems from a range of perspectives, thereby modeling integrated, solution-focused thinking and partnerships.

This book presents the proceedings of the International Conference on Recent Trends in Materials and Devices (ICRTMD 2019) held in India. The conference provides a platform to tackle complex problems from a range of perspectives, thereby modeling integrated, solution-focused thinking and partnerships.

The book contains selected and peer-reviewed papers presented during the ‘International Workshop on Renewable Energy and Storage Devices for Sustainable Development’ (IWRESD-2021).

The book contains selected and peer-reviewed papers presented during the ‘International Workshop on Renewable Energy and Storage Devices for Sustainable Development’ (IWRESD-2021).

This book is a collection of the high-quality research articles presented at the International Conference on Business Intelligence and Data Analytics (BIDA 2024), organized by RV Institute of Management (RVIM), Bengaluru, India, during April 2024. The book covers state-of-the-art research articles from the researchers and practitioners working in the field of business intelligence, data analytics, decision support systems, data warehousing and data mining, big data analytics, predictive and prescriptive analytics, and machine learning for business applications and their real-world applications.