Prithi Samuel – författare

Self-powered Sensors: A Path to Wearable Electronics features recent developments in chemical, photonic, pharmaceutical, microbiological, biomimetic, and bio-inspired approaches for MEMS/NEMS and medicinal self-powered sensors. Unconventional nanomaterial sensors driven by self-sufficient energy are given a contemporary review, with a focus on the categorization of energy sources and comparisons of research involving self-powered solar, piezoresistive, triboelectric, and thermodynamic technologies. This book also focuses on the different techniques, materials, comparisons of fabrication of self-powered sensors as well as thermoelectric self-powered sensors and its implantable applications.Presents state-of-the-art technologies and advancements in the design and application of self-powered sensorsExamines the advantages and disadvantages of self-powered nanomaterial sensors in terms of energy collecting techniques and sensing applicationsReviews the incorporation of self-operating devices and novel uses for neuromorphic sensors

AI-Driven Cybersecurity for Intelligent Healthcare Systems explores the intersection between AI, cybersecurity, and healthcare. The book offers detailed insights into the unique cybersecurity challenges faced by the healthcare sector and the role of AI in addressing these challenges. It presents case studies and real-world applications to illustrate the effectiveness of these solutions and highlights the significance of data privacy in healthcare and methods to ensure secure data sharing and storage. Topics such as federated learning, homomorphic encryption, and blockchain technology are covered to demonstrate how AI can enhance data security without compromising patient privacy.This book will be an essential resource for anyone involved in the healthcare industry, offering practical solutions and fostering a more in-depth understanding of how AI can revolutionize cybersecurity in healthcare.Includes case studies and real-world applications to illustrate the effectiveness of intelligent cybersecurity solutionsDiscusses the increasing integration of artificial intelligence (AI) in healthcare systems, highlighting its role in enhancing medical diagnosis, treatment planning, and patient careFocuses on advanced techniques for enhancing data security while maintaining patient privacy

This book presents a framework for integrating blended learning and massive open online courses (MOOCs) in the Indian education system. It argues that blended teaching and learning is the most suitable approach to education in a post-COVID-19 world. Drawing on case studies used in blended learning practices around the world, the book provides ample resources for beginners to improvise the spread of knowledge around information technology in higher education. It discusses various concepts such as flip learning in blended learning models and examines the self-assessment tools and structures it offers to institutions for building competencies.In addition to addressing the challenges and opportunities of adopting the digital mode of teaching, the book also offers techniques and concepts helpful for designing MOOCs. It covers concepts such as curriculum designing, content flow, teaching behavior, and evaluation patterns, which are important aspects of online teaching. An indispensable guide to navigating the shift from offline to online teaching, this book will be of interest to students, teachers, and researchers of education, education technology, digital education, and information technology. It will also be useful to policymakers, educational institutions, EdTech start-ups, NGOs in the education sector, and online education centers.

This book presents a framework for integrating blended learning and massive open online courses (MOOCs) in the Indian education system. It argues that blended teaching and learning is the most suitable approach to education in a post-COVID-19 world. Drawing on case studies used in blended learning practices around the world, the book provides ample resources for beginners to improvise the spread of knowledge around information technology in higher education. It discusses various concepts such as flip learning in blended learning models and examines the self-assessment tools and structures it offers to institutions for building competencies.In addition to addressing the challenges and opportunities of adopting the digital mode of teaching, the book also offers techniques and concepts helpful for designing MOOCs. It covers concepts such as curriculum designing, content flow, teaching behavior, and evaluation patterns, which are important aspects of online teaching. An indispensable guide to navigating the shift from offline to online teaching, this book will be of interest to students, teachers, and researchers of education, education technology, digital education, and information technology. It will also be useful to policymakers, educational institutions, EdTech start-ups, NGOs in the education sector, and online education centers.

This book is essential for anyone interested in understanding how smart agriculture, utilizing information and technology such as computer vision and deep learning, can revolutionize agriculture productivity, resolve ongoing concerns, and enhance economic and general effectiveness in farming. The need for a reliable food supply has driven the development of smart agriculture, which leverages technology to assist farmers, especially in remote areas. A key component is computer vision (CV) technology, which, combined with deep learning, can manage agricultural productivity and enhance automation systems for improved efficiency and cost-effectiveness. Automation in agriculture ensures benefits like reduced costs, high performance, and accuracy. Aerial imaging and high-throughput research enable effective crop monitoring and management. Computer vision and AI models aid in detecting plant health, impurities, and pests, supporting sustainable farming. This book explores using CV and AI to develop smart agriculture through deep learning, data mining, and intelligent applications.

Comprehensive reference exploring the benefits and implementation of digital twins in industrial production and manufacturing Digital Twins in Industrial Production and Smart Manufacturing provides an overview of digital twin theoretical concepts, techniques, and recent trends used to meet the requirements and challenges of industrial production and smart manufacturing. The text describes how to achieve industrial excellence through virtual factory simulation and digital modeling innovations for next-generation manufacturing system design. The contributing authors address the many possible technical advantages of major Industry 5.0 technological advancements, using illustrations to aid readers in practical implementation of concepts, along with existing scenarios, potential research gaps, adoption difficulties, case studies, and future research objectives. The text also presents many applications and use cases of Industry 5.0 and digital twins in a variety of industries, including the aerospace industry, pharmaceutical manufacturing and biotech, augmented reality, virtual reality, edge computing and blockchain-based Internet of Things (IoT), cobots, intelligent logistics and supply chain management, and more. Edited by a group of highly qualified academics with significant experience in the field, Digital Twins in Industrial Production and Smart Manufacturing covers additional topics such as: Hyper-automation technology, including specialized workflow procedures and particular sectors of solicitations linked to hyper-automationDigital twins in the context of smart cities, with attempts to draw comparisons with the use of digital twins in industrial IoTVirtual factories based on digital twins and corresponding architecture to facilitate modeling, simulation, and assessment of manufacturing systemsCognitive, interactive, and standardization aspects of digital twins, and the proper implementation of digital twin technology for safety critical systemsDigital Twins in Industrial Production and Smart Manufacturing is a must-have reference for researchers, scholars, and professionals in fields related to digital twins in industrial production and manufacturing. It is also suitable as a hands-on resource for students interested in the fields of digital twins and smart manufacturing.

This book explores the distinct problems, trends, and future trajectories for constructing cohesive, sustainable data infrastructures that correspond with the United Nations Sustainable Development Goals (SDGs). In the contemporary digital ecosystem, the amalgamation of data across diverse platforms and environments—from cloud to edge to IoT—has become imperative for fostering creativity, sustainability, and efficiency. “Learning-Driven Data Fabric for Sustainable Cloud-to-Thing Continuum” examines the optimization of integration through sophisticated data fabrics enhanced by machine learning and AI. This book initiates its exploration by analyzing the fundamental concepts of a learning-driven data fabric that integrates cloud and IoT ecosystems, facilitating real-time decision-making and minimizing energy consumption. It offers comprehensive insights into how intelligent data management throughout the cloud-to-thing continuum may be utilized to enhance resource efficiency, facilitate smart city planning, and promote advancements in sectors such as healthcare, transportation, and agriculture. This book emphasizes how data fabrics may advance objectives related to affordable and clean energy (SDG 7), industrial innovation (SDG 9), and sustainable cities and communities (SDG 11), with sustainability as its central theme. This book illustrates how learning-driven data architectures are revolutionizing businesses and tackling global challenges through real-world case studies and upcoming trends. Subjects encompass edge computing, real-time data analytics, safe data transmission, and the reduction of carbon footprints via effective data processing. This study examines how data fabrics might alleviate the risks associated with cyberattacks and data breaches, while ensuring regulatory compliance and fostering sustainable, ethical AI operations. This book offers a detailed framework for utilizing data fabric technologies to create sustainable, safe, and intelligent cloud-to-thing ecosystems, regardless of whether you are a data scientist, IoT specialist, cloud architect, or policymaker. This book promotes data-driven decision-making throughout the infrastructure, enabling organizations to design scalable and sustainable solutions that advance global development objectives.