G. R. Kanagachidambaresan – författare

This reference book explores the integration of cognitive computing technologies in the automotive industry to enhance smart transportation systems. It focuses on how AI, machine learning, and data analytics can improve vehicle automation, safety, and efficiency. Automation can support driverless vehicle transportation and bridge the gap between manual control and fully automated navigation systems. The text introduces a discussion on numerous applications of cognitive computing in smart transportation, motion planning, situation awareness, dynamic driving, adaptive behavior, human intent measurement, and predictive analysis.Key Features:• Discusses basic concepts and architecture of cognitive computing for vehicular systems.• Presents technologies to measure human intent for vehicle safety, including emergency management systems (EMS).• Covers the perception and localization processes in autonomous driving through LiDAR, GPS, and Stereo vision data with critical decision‑making and simulation results.• Elucidates the application of motion planning for smart transportation.• Covers visual perception technologies for advanced driver assistance systems (ADAS) through deep learning.The text is primarily written for graduate students, academic researchers, and professionals in the fields of computer science, electrical engineering, automotive engineering, and civil engineering.

Efficient Single Board Computers (SBCs) and advanced VLSI systems have resulted in edge analytics and faster decision making. The QoS parameters like energy, delay, reliability, security, and throughput should be improved on seeking better intelligent expert systems. The resource constraints in the Edge devices, challenges the researchers to meet the required QoS. Since these devices and components work in a remote unattended environment, an optimum methodology to improve its lifetime has become mandatory. Continuous monitoring of events is mandatory to avoid tragic situations; it can only be enabled by providing high QoS. The applications of IoT in digital twin development, health care, traffic analysis, home surveillance, intelligent agriculture monitoring, defense and all common day to day activities have resulted in pioneering embedded devices, which can offer high computational facility without much latency and delay. The book address industrial problems in designing expert system and IoT applications. It provides novel survey and case study report on recent industrial approach towards Smart City development.

The cognitive approach to the IoT provides connectivity to everyone and everything since IoT connected devices are known to increase rapidly. When the IoT is integrated with cognitive technology, performance is improved, and smart intelligence is obtained. Discussed in this book are different types of datasets with structured content based on cognitive systems. The IoT gathers the information from the real time datasets through the internet, where the IoT network connects with multiple devices.This book mainly concentrates on providing the best solutions to existing real-time issues in the cognitive domain. Healthcare-based, cloud-based and smart transportation-based applications in the cognitive domain are addressed. The data integrity and security aspects of the cognitive computing main are also thoroughly discussed along with validated results.

INTEGRATION OF RENEWABLE ENERGY SOURCES WITH SMART GRID Provides comprehensive coverage of renewable energy and its integration with smart grid technologies. This book starts with an overview of renewable energy technologies, smart grid technologies, and energy storage systems and covers the details of renewable energy integration with smart grid and the corresponding controls. It also provides an enhanced perspective on the power scenario in developing countries. The requirement of the integration of smart grid along with the energy storage systems is deeply discussed to acknowledge the importance of sustainable development of a smart city. The methodologies are made quite possible with highly efficient power convertor topologies and intelligent control schemes. These control schemes are capable of providing better control with the help of machine intelligence techniques and artificial intelligence. The book also addresses modern power convertor topologies and the corresponding control schemes for renewable energy integration with smart grid. The design and analysis of power converters that are used for the grid integration of solar PV along with simulation and experimental results are illustrated. The protection aspects of the microgrid with power electronic configurations for wind energy systems are elucidated. The book also discusses the challenges and mitigation measure in renewable energy integration with smart grid. Audience The core audience is hardware and software engineers working on renewable energy integration related projects, microgrids, smart grids and computing algorithms for converter and inverter circuits. Researchers and students in electrical, electronics and computer engineering will also benefit reading the book.

MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoT’s potential and this book brings clarity to the issue. Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems. Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains.

Rapidly prototype and program new IoT and Edge solutions using low-cost Maker tech, such as those from Arduino, Raspberry Pi and Nvidia. With a focus on the electronics, this book allows experienced computer science students as well as researchers, practitioners, and even hobbyists to dive right into actual engineering of prototypes and not just theoretical programming and algorithms. You'll learn to interface sensors, work with various communication mediums, incorporate wired and wireless communication protocols, and more with these single board computers. All while working in the popular Python programming language. Additionally, you’ll discover both scripting-based and drag and drop solutions for different problems. As well as a variety of useful, data gathering approaches.  Then you can apply what you’ve learned to IoT projects and troubleshooting Industry 4.0 problems. The rapid growth of technology and new development initiatives has made the Internet of Things and Edge analytics an inevitable platform in all engineering domains. The need for sophisticated and ambient environments controlled by tech has resulted in an exponential growth of automation and artificial intelligence. Internet of Things Using Single Board Computers reflects these recent developments while providing a low-cost, easy ramp into the fields of IoT using single board computers and Python programming. What You'll LearnProgram Arduino, Raspberry Pi, and Nvidia boards for rapid prototyping in IoT and Edge environmentsInterface sensors, communication mediums, and wired and wireless communications into your programs and projects.Study practical applications of these low-cost solutions in fields such as home automation, smart cities, electrical vehicle charging, and more.Who This Book is ForEngineers and hobbyists working on Internet of Things prototypes and applications.  Basic skills in electronics and a working knowledge of Python are recommended. Engineers and scientists working on smart environment projects and smart city applications will also benefit.

This book Identifies the right sensors and single board computers for any application to achieve the best performance in Industry 4.0 settings and applications. You’ll see what technologies apply the IIoT with elegant efficiency to drastically improve remote monitoring and controlling, decision making, and preventative maintenance. Start by learning exactly what Industry 4.0 is and advance your knowledge from simple Internet of Things projects to full-on Industrial IoT deployment. You'll automate advanced processes, incorporate professional procedures, and take your IoT skills to a professional level. Then move into the protocols and standards expected for industrial applications of sensors at an industrial level. Match the right SBCs to the right use cases and sensor technologies to optimize efficiency and ensure peak performance. Then move into setting up a smart factory and monitoring your supply chain with tech. Finally, you'll dive into programming with theNode-Red platform and Python packages for CPS.By the end of this book, you’ll have jumped from simple, home-based IoT systems up to industrial and professional applications. Conquer your supply chain and both forward and backward processes with accessible Maker tech! What You'll LearnSupport industrial applications of SBCs and Maker techAchieve peak performance by combining the right sensors with the right processing boardsImprove remote monitoring and controlling drastically for better decision making and preventative maintenance Who This Book Is ForStudents and aspiring professionals working with Internet of things technologies moving towards industrial applications.  Prerequisite knowledge in basic Internet of Things, simple python concepts,  automation, and industry procedures is required for this book.  Engineers and scientists who are pursuing research and contributing to industrial internet of things might also benefit.

This book provides a novel solution for existing challenges in wireless body sensor networks (WBAN) such as network lifetime, fault tolerant approaches, reliability, security, and privacy. The contributors first discuss emerging trends of WBAN in the present health care system. They then provide possible solutions to challenges inherent in WBANs. Finally, they discuss results in working environments. Topics include communication protocols of implanted, wearable and nano body sensor networks; energy harvesting methodologies and experimentation for WBAN; reliability analysis and fault tolerant architecture for WBAN; and handling network failure during critical duration. The contributors consist of researchers and practitioners in WBAN around the world.

This book covers challenges and solutions in establishing Industry 4.0 standards for Internet of Things. The concept of digital twin and complexity in data analytics for predictive maintenance and fault prediction is also covered. It also concentrates on predictive maintenance and predictive failures.

This book covers challenges and solutions in establishing Industry 4.0 standards for Internet of Things. The concept of digital twin and complexity in data analytics for predictive maintenance and fault prediction is also covered. It also concentrates on predictive maintenance and predictive failures.

This book provides solution for challenges facing engineers in urban environments looking towards smart development and IoT. The authors address the challenges faced in developing smart applications along with the solutions. Topics addressed include reliability, security and financial issues in relation to all the smart and sustainable development solutions discussed.  The solutions they provide are affordable, resistive to threats, and provide high reliability. The book pertains to researchers, academics, professionals, and students.Provides solutions to urban sustainable development problems facing engineers in developing and developed countriesDiscusses results with industrial problems and current issues in smart city developmentIncludes solutions that are reliable, secure and financially sound

This book provides solution for challenges facing engineers in urban environments looking towards smart development and IoT. The authors address the challenges faced in developing smart applications along with the solutions. Topics addressed include reliability, security and financial issues in relation to all the smart and sustainable development solutions discussed.  The solutions they provide are affordable, resistive to threats, and provide high reliability. The book pertains to researchers, academics, professionals, and students.Provides solutions to urban sustainable development problems facing engineers in developing and developed countriesDiscusses results with industrial problems and current issues in smart city developmentIncludes solutions that are reliable, secure and financially sound

Topics include IoT Applications for eHealth, smart environments, intelligent transportation systems, delay tolerant models for IoT applications, protocols and architectures for industrial IoT, energy efficient protocols, and much more.

Topics include IoT Applications for eHealth, smart environments, intelligent transportation systems, delay tolerant models for IoT applications, protocols and architectures for industrial IoT, energy efficient protocols, and much more.

This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics.

This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics.

This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in deep learning. The authors start with the fundamentals, architectures, tools needed for effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python. They proceed with advanced concepts with hands-on sessions for deep learning. Engineers, scientists, researches looking for a practical approach to deep learning will enjoy this book.Presents practical basics to advanced concepts in deep learning and how to apply them through various projects;Discusses topics such as deep learning in smart grids and renewable energy & sustainable development;Explains how to implement advanced techniques in deep learning using Pytorch, Keras, Python programming.

This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in deep learning. The authors start with the fundamentals, architectures, tools needed for effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python. They proceed with advanced concepts with hands-on sessions for deep learning. Engineers, scientists, researches looking for a practical approach to deep learning will enjoy this book.Presents practical basics to advanced concepts in deep learning and how to apply them through various projects;Discusses topics such as deep learning in smart grids and renewable energy & sustainable development;Explains how to implement advanced techniques in deep learning using Pytorch, Keras, Python programming.

This book discusses advances in smart and sustainable development of smart environments. Topics include health care applications, sustainable smart transportation systems, intelligent sustainable wearable electronics, and sustainable smart building and alert systems.

This book discusses advances in smart and sustainable development of smart environments. Topics include health care applications, sustainable smart transportation systems, intelligent sustainable wearable electronics, and sustainable smart building and alert systems.

This book presents how to program Single Board Computers (SBCs) for Internet of Things (IoT) rapid prototyping with popular tools such as Raspberry Pi, Arduino, Beagle Bone, and NXP boards. The aim of the book is to provide programming, sensors interfacing, PCB design, and Mechanical Cad design to and create rapid prototyping.

This book presents how to program Single Board Computers (SBCs) for Internet of Things (IoT) rapid prototyping with popular tools such as Raspberry Pi, Arduino, Beagle Bone, and NXP boards. The aim of the book is to provide programming, sensors interfacing, PCB design, and Mechanical Cad design to and create rapid prototyping.

The book provides easy interpretable explanations for the key technologies involved in Electric Vehicles and Hybrid Electric Vehicles.

The book provides easy interpretable explanations for the key technologies involved in Electric Vehicles and Hybrid Electric Vehicles.

This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications.