Lalit Garg – författare

Intelligent Biomedical Technologies and Applications for Healthcare 5.0, Volume Sixteen covers artificial health intelligence, biomedical image analysis, 5G, the Internet of Medical Things, intelligent healthcare systems, and extended health intelligence (EHI). This volume contains four sections. The focus of the first section is health data analytics and applications. The second section covers research on information exchange and knowledge sharing. The third section is on the Internet of Things (IoT) and the Internet of Everything (IoE)-based solutions. The final section focuses on the implementation, assessment, adoption, and management of healthcare informatics solutions.This new volume in the Advances in Ubiquitous Sensing Applications for Healthcare series focuses on innovative methods in the healthcare industry and will be useful for biomedical engineers, researchers, and students working in interdisciplinary fields of research. This volume bridges these newly developing technologies and the medical community in the rapidly developing healthcare world, introducing them to modern healthcare advances such as EHI and Smart Healthcare Systems.

Since the invention of computers and other similar machines, scientists and researchers have been trying very hard to enhance their capabilities to perform various tasks. As a result, the capabilities of computers are growing exponentially day by day in terms of diverse working domains, versatile jobs, processing speed, and reduced size. Now, we are in the race to make these machines as intelligent as human beings. Artificial intelligence (AI) came up as a way of making a computer or computer software think in a similar manner to the way that humans think. AI is inspired by the study of human brain, including how humans think, learn, decide, and act while trying to solve a problem. The outcomes of this study are the basis of developing intelligent software and systems or intelligent computing (IC).

An IC system has the capabilities of reasoning, learning, problem-solving, perception, and linguistic intelligence. IC systems consist of AI techniques as well as other emerging techniques that make a system intelligent. The use of IC has been seen in almost every sub-domain of computer science such as networking, software engineering, gaming, natural language processing, computer vision, image processing, data science, robotics, expert systems, and security. Nowadays, IC is also useful for solving various complex problems in diverse domains such as for predicting disease in medical science, predicting land fertility or crop productivity in agricultural science, predicting market growth in economics, and weather forecasting.

For all these reasons, this book presents the advances in AI techniques, under the umbrella of IC. In this context, the book includes recent research that has been done in the areas of machine learning, neural networks, deep learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems, and so on. This book discusses recent theoretical, algorithmic, simulation, and implementation-based advancements related to IC.

Since the invention of computers and other similar machines, scientists and researchers have been trying very hard to enhance their capabilities to perform various tasks. As a result, the capabilities of computers are growing exponentially day by day in terms of diverse working domains, versatile jobs, processing speed, and reduced size. Now, we are in the race to make these machines as intelligent as human beings. Artificial intelligence (AI) came up as a way of making a computer or computer software think in a similar manner to the way that humans think. AI is inspired by the study of human brain, including how humans think, learn, decide, and act while trying to solve a problem. The outcomes of this study are the basis of developing intelligent software and systems or intelligent computing (IC).

An IC system has the capabilities of reasoning, learning, problem-solving, perception, and linguistic intelligence. IC systems consist of AI techniques as well as other emerging techniques that make a system intelligent. The use of IC has been seen in almost every sub-domain of computer science such as networking, software engineering, gaming, natural language processing, computer vision, image processing, data science, robotics, expert systems, and security. Nowadays, IC is also useful for solving various complex problems in diverse domains such as for predicting disease in medical science, predicting land fertility or crop productivity in agricultural science, predicting market growth in economics, and weather forecasting.

For all these reasons, this book presents the advances in AI techniques, under the umbrella of IC. In this context, the book includes recent research that has been done in the areas of machine learning, neural networks, deep learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems, and so on. This book discusses recent theoretical, algorithmic, simulation, and implementation-based advancements related to IC.

In current digital era, information is an important asset for our daily life as well as for small and large-scale businesses. The network technologies are the main enablers that connect the computing devices and resources together to collect, process and share vital information locally as well as globally. The network technologies provide efficient, flexible and seamless communication while maximizing productivity and resources for our day-to-day lives and business operations. For all its importance, this domain has evolved drastically, from the traditional wired networks to Bluetooth, infrared-waves, micro-waves, radio-waves and satellite networks. Nowadays, network technologies are not only restricted to computer laboratories, offices or homes; many other diverse areas have been witnessed where network technologies are being used based on the applications and needs, such as vehicular ad-hoc networks, underwater networks, and the Internet of Things.

Along with the hardware-based and physical network technologies, a lot of research has been carried out by researchers from academia and industry to develop emerging software-based network technologies, such as network software architectures, middleware, and protocol stacks. The software-based network technologies become the main driving force behind the paradigm shift in this domain and have invented many new network technologies such as grid computing, cloud computing, fog computing, edge computing, software defined networks, content centric networks and so on. On the other hand, a lot of efforts have been made in cellular network technologies to improve the user experience and as a consequence, emerging cellular network technologies like LTE, VoLTE and 5G have been invented. Due to its demand and importance in present and future scenarios, numerous efforts have been done in the networking domain by the researchers, a lot of work is still ongoing, and many more possibilities have yet to be explored. Therefore, there is a need to keep track of advancements related to the network technologies and further investigate several ongoing research challenges for the ease of users. With this goal in mind, Research Advances in Network Technologies presents the most recent and notable research on network technologies.

In current digital era, information is an important asset for our daily life as well as for small and large-scale businesses. The network technologies are the main enablers that connect the computing devices and resources together to collect, process and share vital information locally as well as globally. The network technologies provide efficient, flexible and seamless communication while maximizing productivity and resources for our day-to-day lives and business operations. For all its importance, this domain has evolved drastically, from the traditional wired networks to Bluetooth, infrared-waves, micro-waves, radio-waves and satellite networks. Nowadays, network technologies are not only restricted to computer laboratories, offices or homes; many other diverse areas have been witnessed where network technologies are being used based on the applications and needs, such as vehicular ad-hoc networks, underwater networks, and the Internet of Things.

Along with the hardware-based and physical network technologies, a lot of research has been carried out by researchers from academia and industry to develop emerging software-based network technologies, such as network software architectures, middleware, and protocol stacks. The software-based network technologies become the main driving force behind the paradigm shift in this domain and have invented many new network technologies such as grid computing, cloud computing, fog computing, edge computing, software defined networks, content centric networks and so on. On the other hand, a lot of efforts have been made in cellular network technologies to improve the user experience and as a consequence, emerging cellular network technologies like LTE, VoLTE and 5G have been invented. Due to its demand and importance in present and future scenarios, numerous efforts have been done in the networking domain by the researchers, a lot of work is still ongoing, and many more possibilities have yet to be explored. Therefore, there is a need to keep track of advancements related to the network technologies and further investigate several ongoing research challenges for the ease of users. With this goal in mind, Research Advances in Network Technologies presents the most recent and notable research on network technologies.

Cloud and Fog Optimization-based Solutions for Sustainable Developments discusses the integration of fog computing and the Internet of Things to provide scalable, secure, and cost-effective digital infrastructures for smart services in diverse domains:

The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

Cloud and Fog Optimization-based Solutions for Sustainable Developments discusses the integration of fog computing and the Internet of Things to provide scalable, secure, and cost-effective digital infrastructures for smart services in diverse domains:

The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

This is the proceedings of the 1st International Conference on Applications of AI in 5G and IoT (ICAAI5GI2024). It brings together ground-breaking research and practical insights into integrating Artificial Intelligence within 5G and the Internet of Things (IoT).

This compilation highlights the latest advancements and innovative solutions emerging at the intersection of AI, 5G, and IoT technologies. It also delves into a wide array of topics, including the role of AI in enhancing 5G network efficiency, the development of intelligent IoT devices, and the creation of smart environments powered by these cutting-edge technologies. It further showcases key findings on AI-driven applications in 5G for seamless communication, improved connectivity, and advanced data processing techniques, along with IoT solutions for smart cities, industrial automation, healthcare, and beyond.

It would be a valuable read for researchers, engineers, and professionals in AI, 5G, IoT, and related fields. It serves as an essential resource for those seeking to stay at the forefront of technological advancements in these rapidly evolving domains.

This is the proceedings of the 1st International Conference on Applications of AI in 5G and IoT (ICAAI5GI2024). It brings together ground-breaking research and practical insights into integrating Artificial Intelligence within 5G and the Internet of Things (IoT).

This compilation highlights the latest advancements and innovative solutions emerging at the intersection of AI, 5G, and IoT technologies. It also delves into a wide array of topics, including the role of AI in enhancing 5G network efficiency, the development of intelligent IoT devices, and the creation of smart environments powered by these cutting-edge technologies. It further showcases key findings on AI-driven applications in 5G for seamless communication, improved connectivity, and advanced data processing techniques, along with IoT solutions for smart cities, industrial automation, healthcare, and beyond.

It would be a valuable read for researchers, engineers, and professionals in AI, 5G, IoT, and related fields. It serves as an essential resource for those seeking to stay at the forefront of technological advancements in these rapidly evolving domains.

The multimodal and multimedia data need to be secured and preserved properly in the present scenario. The methodologies proposed in the book will offer a new paradigm in AI-based techniques. With these approaches, the social good of modern society will be enhanced. Multimedia, multimodal data and intelligent systems will deliver insightful comments for sustainable development. Therefore, these challenges have proven exciting for multimedia and multimodal AI researchers. These facts served as the impetus for the writing of this book, which is intended for researchers who fulfill modern society’s requirements.

Key Features:

The book can be used as a reference book for practicing engineers, scientists, researchers and technologists. It will also be helpful for senior undergraduate and graduate students, practitioners from government and industry and professionals working on state-of-the-art multimedia and multimodal intelligence solutions for modern society applications.

Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science, bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis.

This book provides innovative insights that will help obtain interventions to undertake emerging dynamic scenarios of criminal activities. Furthermore, it presents emerging issues, challenges and management strategies in public safety and crime control development across various domains. The book will play a vital role in improvising human life to a great extent. Researchers and practitioners working in the fields of data mining, machine learning and artificial intelligence will greatly benefit from this book, which will be a good addition to the state-of-the-art approaches collected for intelligent data analytics. It will also be very beneficial for those who are new to the field and need to quickly become acquainted with the best performing methods. With this book they will be able to compare different approaches and carry forward their research in the most important areas of this field, which has a direct impact on the betterment of human life by maintaining the security of our society. No other book is currently on the market which provides such a good collection of state-of-the-art methods for intelligent data analytics-based models for terror threat prediction, as intelligent data analytics is a newly emerging field and research in data mining and machine learning is still in the early stage of development.

Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science, bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis.

This book provides innovative insights that will help obtain interventions to undertake emerging dynamic scenarios of criminal activities. Furthermore, it presents emerging issues, challenges and management strategies in public safety and crime control development across various domains. The book will play a vital role in improvising human life to a great extent. Researchers and practitioners working in the fields of data mining, machine learning and artificial intelligence will greatly benefit from this book, which will be a good addition to the state-of-the-art approaches collected for intelligent data analytics. It will also be very beneficial for those who are new to the field and need to quickly become acquainted with the best performing methods. With this book they will be able to compare different approaches and carry forward their research in the most important areas of this field, which has a direct impact on the betterment of human life by maintaining the security of our society. No other book is currently on the market which provides such a good collection of state-of-the-art methods for intelligent data analytics-based models for terror threat prediction, as intelligent data analytics is a newly emerging field and research in data mining and machine learning is still in the early stage of development.

Discusses both theoretical and practical aspects of how to harness advanced technologies to develop practical applications such as drone-based surveillance, smart transportation, healthcare, farming solutions, and robotics used in automation.

The concepts of machine intelligence, big data analytics, and the Internet of Things (IoT) continue to improve our lives through various cutting-edge applications such as disease detection in real-time, crop yield prediction, smart parking, and so forth. The transformative effects of these technologies are life-changing because they play an important role in demystifying smart healthcare, plant pathology, and smart city/village planning, design and development. This book presents a cross-disciplinary perspective on the practical applications of machine intelligence, big data analytics, and IoT by compiling cutting-edge research and insights from researchers, academicians, and practitioners worldwide. It identifies and discusses various advanced technologies, such as artificial intelligence, machine learning, IoT, image processing, network security, cloud computing, and sensors, to provide effective solutions to the lifestyle challenges faced by humankind.

Machine Intelligence, Big Data Analytics, and IoT in Image Processing is a significant addition to the body of knowledge on practical applications emerging from machine intelligence, big data analytics, and IoT. The chapters deal with specific areas of applications of these technologies. This deliberate choice of covering a diversity of fields was to emphasize the applications of these technologies in almost every contemporary aspect of real life to assist working in different sectors by understanding and exploiting the strategic opportunities offered by these technologies.

Audience

The book will be of interest to a range of researchers and scientists in artificial intelligence who work on practical applications using machine learning, big data analytics, natural language processing, pattern recognition, and IoT by analyzing images. Software developers, industry specialists, and policymakers in medicine, agriculture, smart cities development, transportation, etc. will find this book exceedingly useful.