Amrita Rai - Böcker

This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures.

This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures.

The book explores the intricate nexus between biometric systems and the need for preserving data integrity as well as security needed during the data communication. It offers a systematic and insightful journey through the multifaceted landscape of biometrics, emphasizing the development of resilient systems and the judicious preservation of critical data.The book starts with introduction to biometric systems, unravelling the intricacies of various authentication methods and technologies. Delving into the principles of robust biometric authentication, the authors elucidate cutting-edge techniques designed to withstand evolving security challenges. It then addresses the pivotal role of data preservation in the context of biometric systems and security system from encryption methodologies that fortify the security of biometric data to innovative approaches in data security and preservation, each chapter delves into the nuanced intricacies of maintaining data integrity. The authors navigate through the challenges associated with biometric data storage and propose solutions that align with contemporary technological advancements. The integration of case studies, practical examples, and real-world applications enhances the reader's understanding, fostering a hands-on approach to the implementation of robust biometric systems. The concluding chapters review the future of biometric systems, exploring emerging trends and potential advancements on the horizon. The book strikes a balance between theoretical concepts and practical considerations, making it an indispensable resource for those seeking a holistic understanding of biometric systems and efficient data preservation.The content caters to a diverse audience, including researchers, practitioners, and students interested in biometrics, data security, IoT based security system design.

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.

The book offers valuable insights into research related to Industry 4.0 applications that utilize artificial intelligence (AI), machine learning (ML), and the Industrial Internet of Things (IIoT). Industry 4.0, also known as the Fourth Industrial Revolution, includes disruptive technologies such as the Internet of Things (IoT), robotics, virtual reality (VR), VLSI architecture, and AI, all of which are transforming modern society and manufacturing practices. This book addresses various aspects of smart industrial application design strategies and their effects on next-generation systems, including quantum computing, edge computing, IoT, cybersecurity, nano-communications, and robotic automation. The application of AI, machine learning techniques, and IoT is anticipated to improve the performance of automated and controlled systems. Intended as a resource for academics, researchers, and professionals in the fields of AI and ML, the content also explores their applications within the industrial revolution and the influence of VLSI on the global market. Additionally, the book serves as a reference for developing sustainable engineering solutions to address various global industrial challenges.

This book focuses on both theory and applications of Artificial Intelligence and Machine Learning in the broad areas of communication and networking.