Biswaranjan Acharya – författare

AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-based data analytics and IoT for predictability of crop, soil, and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management, and smart farming. The book provides an overarching focus on sustainable environment and sustainable economic development through smart and e-agriculture.

Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture and data mining researchers around the world provide foundational insights. The book provides practical application opportunities for the resolution of real-world problems, including contributions from the data mining, data analytics, Edge of Things, and cloud research communities working in the farming production sector. The book offers broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT-based agriculture, Edge of Things and cloud-based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture toward smart farming.

This book addresses the needs of researchers on the fundamental level as well as those with more advanced knowledge of microgrids and their evolution. This book covers newly emerging trends in fields such as computer science, energy, electrical engineering, and electronics and brings the reader current on the newly emerging fields that play an important role in the power infrastructure.

Microgrids: Design, Challenges, and Prospects provides knowledge on decision making for newly evolving trends in microgrid design. It discusses techniques on how to improve the existing power quality and reduce load shedding and power imbalances. The book presents the emerging fields such as data science, machine learning, AI, and IT that now play an important role in microgrid design. The readership includes: researchers, academia, practicing engineers, consumers, power companies, and policy makers located across the globe.

This book addresses the needs of researchers on the fundamental level as well as those with more advanced knowledge of microgrids and their evolution. This book covers newly emerging trends in fields such as computer science, energy, electrical engineering, and electronics and brings the reader current on the newly emerging fields that play an important role in the power infrastructure.

Microgrids: Design, Challenges, and Prospects provides knowledge on decision making for newly evolving trends in microgrid design. It discusses techniques on how to improve the existing power quality and reduce load shedding and power imbalances. The book presents the emerging fields such as data science, machine learning, AI, and IT that now play an important role in microgrid design. The readership includes: researchers, academia, practicing engineers, consumers, power companies, and policy makers located across the globe.

Natural Language Processing In Healthcare: A Special Focus on Low Resource Languages covers the theoretical and practical aspects as well as ethical and social implications of NLP in healthcare. It showcases the latest research and developments contributing to the rising awareness and importance of maintaining linguistic diversity. The book goes on to present current advances and scenarios based on solutions in healthcare and low resource languages and identifies the major challenges and opportunities that will impact NLP in clinical practice and health studies.

Natural Language Processing In Healthcare: A Special Focus on Low Resource Languages covers the theoretical and practical aspects as well as ethical and social implications of NLP in healthcare. It showcases the latest research and developments contributing to the rising awareness and importance of maintaining linguistic diversity. The book goes on to present current advances and scenarios based on solutions in healthcare and low resource languages and identifies the major challenges and opportunities that will impact NLP in clinical practice and health studies.

This reference text addresses the importance of smart crop management for increasing yield and presents a framework for smart monitoring and regulation of crop observation. Further, it comprehensively covers important topics such as spatial decision support systems for precision farming, swarm intelligence in the optimal management of aquaculture farms, and intelligent harvesting algorithms for improving productivity.

This book:

• Presents meta-heuristic algorithms for optimization, economic crop planning, and use of effective water resource management.

• Discusses spatial decision support systems for crop productivity management, watershed management, and precision farming.

• Illustrates swarm intelligence-based optimization techniques, data mining, and machine learning methods for aquaculture operations.

• Highlights artificial intelligence and machine learning-based harvesting algorithms for improving productivity.

• Explains the use of green Internet of Things security solutions for agriculture, plant condition management, and greenhouse simulation.

It is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, agricultural science, and information technology.

This reference text addresses the importance of smart crop management for increasing yield and presents a framework for smart monitoring and regulation of crop observation. Further, it comprehensively covers important topics such as spatial decision support systems for precision farming, swarm intelligence in the optimal management of aquaculture farms, and intelligent harvesting algorithms for improving productivity.

This book:

• Presents meta-heuristic algorithms for optimization, economic crop planning, and use of effective water resource management.

• Discusses spatial decision support systems for crop productivity management, watershed management, and precision farming.

• Illustrates swarm intelligence-based optimization techniques, data mining, and machine learning methods for aquaculture operations.

• Highlights artificial intelligence and machine learning-based harvesting algorithms for improving productivity.

• Explains the use of green Internet of Things security solutions for agriculture, plant condition management, and greenhouse simulation.

It is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, agricultural science, and information technology.

Decision Support System for Diabetes Healthcare: Advancements and Applications is a comprehensive guide to the cutting-edge technology transforming diabetes management. In this book, leading experts in the field explore how decision support systems (DSS) are revolutionizing healthcare practices, particularly in diabetes care. From advanced data analytics to personalized treatment recommendations, this book delves into the innovative solutions that are reshaping how healthcare providers approach diabetes management. Readers will gain insights into the latest developments in DSS technology, including predictive modeling, machine learning algorithms, and real-time monitoring systems, all designed to enhance patient outcomes and improve quality of life.

With a focus on practical applications, Decision Support System for Diabetes Healthcare offers case studies and examples of successful DSS implementations across various healthcare settings. Whether you''re a healthcare professional, researcher, or technology enthusiast, this book provides invaluable insights into the future of diabetes care. By exploring the intersection of technology and healthcare, readers will discover how DSS is empowering both patients and providers to make informed decisions, optimize treatment plans, and ultimately, transform the way diabetes is managed on a global scale.

Decision Support System for Diabetes Healthcare: Advancements and Applications is a comprehensive guide to the cutting-edge technology transforming diabetes management. In this book, leading experts in the field explore how decision support systems (DSS) are revolutionizing healthcare practices, particularly in diabetes care. From advanced data analytics to personalized treatment recommendations, this book delves into the innovative solutions that are reshaping how healthcare providers approach diabetes management. Readers will gain insights into the latest developments in DSS technology, including predictive modeling, machine learning algorithms, and real-time monitoring systems, all designed to enhance patient outcomes and improve quality of life.

With a focus on practical applications, Decision Support System for Diabetes Healthcare offers case studies and examples of successful DSS implementations across various healthcare settings. Whether you''re a healthcare professional, researcher, or technology enthusiast, this book provides invaluable insights into the future of diabetes care. By exploring the intersection of technology and healthcare, readers will discover how DSS is empowering both patients and providers to make informed decisions, optimize treatment plans, and ultimately, transform the way diabetes is managed on a global scale.

The book will help the readers in the field of the Internet of Things, and especially its convergence with artificial intelligence, which has given rise to the new paradigm of artificial intelligence of things (AIoT). It covers important concepts such as intelligent space and human-centered robotics and its effect on human wellbeing, and human-centered aviation automation.

This book:

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

The book will help the readers in the field of the Internet of Things, and especially its convergence with artificial intelligence, which has given rise to the new paradigm of artificial intelligence of things (AIoT). It covers important concepts such as intelligent space and human-centered robotics and its effect on human wellbeing, and human-centered aviation automation.

This book:

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

This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing.

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