Anand Nayyar

Mohd Naved

Joanna Rosak-Szyrocka

Justyna Żywiołek

This book is devoted to the issues faced by universities in the field of distance learning during and after COVID, as well as in digitalization times. The book devotes a lot of space to the issues of Web 3.0 in university e-learning, Industry 4.0, artificial intelligence and digital equity. The aim and scope of this book is to draw a holistic picture of education before and after COVID, the psychological effects of COVID in education, and using modern technologies application in education, taking into consideration aspects of sustainability development, Industry 4.0 and Society 5.0. The authors also raise the issue of artificial intelligence investigation in learner-instructor interaction. Features: • To elaborate the functions of online education and numerous pedagogical strategies based on electronic learning to aid teachers and students with the tools required to succeed in the 21st century via engaging virtual experiences • To analyze tools provided by Ed-Tech firms and the effect of digital tools on maintaining the educational process in times of crisis and after pandemic • To create a roadmap for higher education institutions and provide tips regarding how to improve the effectiveness of the hybrid learning system • To understand e-learning characteristic in the era of Industry 4.0 and Society 5.0 and characteristics of the different web generations • To use AI applications to improve connections and relationships between students and teachers and in education in the future The book is both scientific and educational. It can be used at the university level and by anyone interested in the topics it covers.

The Role of Sustainability and Artificial Intelligence in Education Improvement

Sudeep Tanwar

Rudra Rameshwar

Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML, as the driving force of the wave of artificial intelligence (AI), provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML, and its aim to solve some of the biggest challenges in AI and ML. FEATURES Focuses on addressing the missing connection between signal processing and ML Provides a one-stop guide reference for readers Oriented toward material and flow with regards to general introduction and technical aspects Comprehensively elaborates on the material with examples and diagrams This book is a complete resource designed exclusively for advanced undergraduate students, post-graduate students, research scholars, faculties, and academicians of computer science and engineering, computer science and applications, and electronics and telecommunication engineering.

Applications, Challenges, and the Road Ahead

Machine Learning in Signal Processing

Kavita Sharma

Kiran Ahuja

Comprehensive Guide to Heterogeneous Networks discusses the fundamental motivations behind this cutting-edge development, along with a brief discussion on the diverse definitions of HNs. The future of heterogeneous wireless networks (HWNs) is covered, including test cases, cost configuration, economic benefits and basic challenges. Other sections cover the topology management method in context of heterogeneous sensor nodes with diverse communication and sensing range. In addition, an outline of the pros and cons of the clustering criteria in HWSNs and taxonomy are summarized and provide futuristic research directions. Final sections discuss the future evolution of HNs and their implementations in diverse applications. This is an essential reference book for advanced students on courses in wireless communications, clinical engineering and networking. It will also be of interest to researchers, network planners, technical mangers and other professionals in these fields. Discusses the most important problems, challenges and issues which arise when designing real-time heterogeneous networks for diverse scenarios Represents the unique features of heterogeneous sensor networks, giving the end-user a better understanding of the environment Provides an overview of real-time performance issues in heterogeneous networks, specifically multi-tasking, multi-level scheduling, localization and security issues Includes applications of heterogeneous networks in diverse fields and focuses on the convergence of heterogeneous wireless networks for 5G

Comprehensive Guide to Heterogeneous Networks

Sanjeevikumar Padmanaban

Sailesh Iyer

This book intends to explore new and innovative ways of conserving Energy, Effective e-waste management and Renewable Energy Sources to harness and nurture a sustainable ecosystem.

Green Energy and Sustainable Ecosystem: Concepts, Principles and Best Practices

Arun Solanki

Sambit Kumar Mishra

Kshira Sagar Sahoo

Bibhudatta Sahoo

SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems. Features: The book covers emerging trends, issues and solutions in the direction of Edge-cloud interplay. It highlights the research advances in on SDN, edge, and IoT architecture for smart cities, and software-defined internet of vehicles. It includes detailed discussion has made of performance evaluations of SDN controllers, scalable software-defined edge computing, and AI for edge computing. Applications areas include machine learning and deep learning in SDN-supported edge-cloud systems. Different use cases covered include smart health care, smart city, internet of drones, etc. This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.

SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things

Dac-Nhuong Le

Nhu Gia Nguyen

This book provides comprehensive details of all Swarm Intelligence based Techniques available till date in a comprehensive manner along with their mathematical proofs. It will act as a foundation for authors, researchers and industry professionals. This monograph will present the latest state of the art research being done on varied Intelligent Technologies like sensor networks, machine learning, optical fiber communications, digital signal processing, image processing and many more.

Advances in Swarm Intelligence for Optimizing Problems in Computer Science

Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative Adversarial Networks for Image-to-Image Translation provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from the original GAN network to various GAN-based systems such as Deep Convolutional GANs (DCGANs), Conditional GANs (cGANs), StackGAN, Wasserstein GANs (WGAN), cyclical GANs, and many more. The book also provides readers with detailed real-world applications and common projects built using the GAN system with respective Python code. A typical GAN system consists of two neural networks, i.e., generator and discriminator. Both of these networks contest with each other, similar to game theory. The generator is responsible for generating quality images that should resemble ground truth, and the discriminator is accountable for identifying whether the generated image is a real image or a fake image generated by the generator. Being one of the unsupervised learning-based architectures, GAN is a preferred method in cases where labeled data is not available. GAN can generate high-quality images, images of human faces developed from several sketches, convert images from one domain to another, enhance images, combine an image with the style of another image, change the appearance of a human face image to show the effects in the progression of aging, generate images from text, and many more applications. GAN is helpful in generating output very close to the output generated by humans in a fraction of second, and it can efficiently produce high-quality music, speech, and images. Introduces the concept of Generative Adversarial Networks (GAN), including the basics of Generative Modelling, Deep Learning, Autoencoders, and advanced topics in GAN Demonstrates GANs for a wide variety of applications, including image generation, Big Data and data analytics, cloud computing, digital transformation, E-Commerce, and Artistic Neural Networks Includes a wide variety of biomedical and scientific applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing, and disease diagnosis Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable GANs for their applications

Generative Adversarial Networks for Image-to-Image Translation

Adarsh Kumar

DIGITAL CITIES ROADMAP This book details applications of technology to efficient digital city infrastructure and its planning, including smart buildings. Rapid urbanization, demographic changes, environmental changes, and new technologies are changing the views of urban leaders on sustainability, as well as creating and providing public services to tackle these new dynamics. Sustainable development is an objective by which the processes of planning, implementing projects, and development is aimed at meeting the needs of modern communities without compromising the potential of future generations. The advent of Smart Cities is the answer to these problems. Digital Cities Roadmap provides an in-depth analysis of design technologies that lay a solid foundation for sustainable buildings. The book also highlights smart automation technologies that help save energy, as well as various performance indicators needed to make construction easier. The book aims to create a strong research community, to have a deep understanding and the latest knowledge in the field of energy and comfort, to offer solid ideas in the nearby future for sustainable and resilient buildings. These buildings will help the city grow as a smart city. The smart city has also a focus on low energy consumption, renewable energy, and a small carbon footprint. Audience The information provided in this book will be of value to researchers, academicians and industry professionals interested in IoT-based architecture and sustainable buildings, energy efficiency and various tools and methods used to develop green technologies for construction in smart cities.

IoT-Based Architecture and Sustainable Buildings

Digital Cities Roadmap

Doctoral Thesis / Dissertation from the year 2017 in the subject Computer Science - Miscellaneous, , course: Ph.D Computer Science, language: English, abstract: Routing and Energy Efficiency is regarded as highly challenging area of Sensor networks. Significant advancements in Wireless Sensor Networks (WSNs) opens doors for wide implementation in real-time applications like Industrial Monitoring, Smart Cities development, Underwater monitoring operations, tracking objects and many more. Energy Efficient routing is regarded as the most challenging task. Sensor networks mostly operate in complex and dynamic environments and routing becomes tedious task to maintain as the network size increases. Lots of routing protocols- Reactive, Proactive and Hybrid are proposed by researchers but every protocol faces some limitations in terms of energy, routing, packet delivery ratio and security. Therefore, to overcome all the routing issues, the trend has shifted to Biological based Algorithms like Swarm Intelligence based techniques. Ant Colony Optimization based routing protocols have demonstrated exceptional results in terms of performance when applied to WSN routing. This thesis outlines routing protocols in sensor networks, highlight the concept of Swarm Intelligence and presents various Ant Colony Optimization based routing protocols for sensor networks. In addition to this, we present Ant Colony based Energy Efficient routing protocol (IEEMARP = Improvised Energy Efficient Multipath Ant Based Routing Protocol) for sensor networks. The proposed protocol takes into consideration various performance metrics like Packet Delivery Ratio, Throughput, Energy Efficiency, Routing Overhead and End-to-End delay. Proposed protocol is simulated and tested using NS-2.35 simulator. Simulation based results stated that IEEMARP routing protocol is overall 16% more efficient in terms of Packet delivery ratio, Energy Efficiency, Throughput, Routing Overhead and End-to-End delay as compared to other ACO based routing protocols. In addition to this, IEEMARP is highly reliable protocol to ensure timely delivery with acknowledgement packet exchange between source node to sink node and vice versa and also combats the issue of congestion and packet dropping to large extent.

Improvised Energy Efficient Routing Protocol based on Ant Colony Optimization (ACO) for Wireless Sensor Networks

Krishna Kant Singh

Mohamed Abouhawwash

Cyber-Physical Systems (CPS) integrate computing and communication capabilities by monitoring and controlling the physical systems via embedded hardware and computers. This book brings together new and futuristic findings on IoT, Cyber Physical Systems and Robotics leading towards Automation and solving issues of various critical applications in Real-time. The book initially overviews the concepts of IoT, IIoT and Cyber Physical Systems followed by various critical applications and discusses the latest designs and developments that provide common solutions for the convergence of technologies. In addition, the book specifies methodologies, algorithms and other relevant architectures in various fields that include Automation, Robotics, Smart Agriculture and Industry 4.0. The book is intended for practitioners, enterprise representatives, scientists, students and Ph.D Scholars in hopes of steering research further towards cyber physical systems design and development and implementation across various domains. Additionally, this book can be used as a secondary reference, or rather one-stop guide, by professionals for real-life implementation of cyber physical systems. The book highlights: " A Critical Coverage of various domains: IoT, Cyber Physical Systems, Industry 4.0, Smart Automation and related critical applications. " Advanced elaborations for target audiences to understand the conceptual methodology and future directions of cyber physical systems and IoT. " An approach towards Research Orientations to enable researchers to point out areas and scope for implementation of Cyber Physical Systems in several domains for better productivity. .

Anand Nayyar

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