Computational Intelligence In Automotive Applications
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Computational Intelligence in Automotive Applications by Danil Prokhorov Pdf
What is computational intelligence (CI)? Traditionally, CI is understood as a collection of methods from the ?elds of neural networks (NN), fuzzy logic and evolutionary computation. Various de?nitions and opinions exist, but what belongs to CI is still being debated; see, e.g., [1–3]. More recently there has been a proposal to de?ne the CI not in terms of the tools but in terms of challenging problems to be solved [4]. With this edited volume I have made an attempt to give a representative sample of contemporary CI activities in automotive applications to illustrate the state of the art. While CI researchand achievements in some specialized ?elds described (see, e.g., [5, 6]), this is the ?rst volume of its kind dedicated to automotive technology. As if re?ecting the general lack of consensus on what constitutes the ?eld of CI, this volume 1 illustrates automotive applications of not only neural and fuzzy computations which are considered to be the “standard” CI topics, but also others, such as decision trees, graphicalmodels, Support Vector Machines (SVM), multi-agent systems, etc. This book is neither an introductory text, nor a comprehensive overview of all CI research in this area. Hopefully, as a broad and representative sample of CI activities in automotive applications, it will be worth reading for both professionals and students. When the details appear insu?cient, the reader is encouraged to consult other relevant sources provided by the chapter authors.
Computational Intelligence in Emerging Technologies for Engineering Applications by Orestes Llanes Santiago,Carlos Cruz Corona,Antônio José Silva Neto,José Luis Verdegay Pdf
This book explores applications of computational intelligence in key and emerging fields of engineering, especially with regard to condition monitoring and fault diagnosis, inverse problems, decision support systems and optimization. These applications can be beneficial in a broad range of contexts, including: water distribution networks, manufacturing systems, production and storage of electrical energy, heat transfer, acoustic levitation, uncertainty and robustness of infinite-dimensional objects, fatigue failure prediction, autonomous navigation, nanotechnology, and the analysis of technological development indexes. All applications, mathematical and computational tools, and original results are presented using rigorous mathematical procedures. Further, the book gathers contributions by respected experts from 22 different research centers and eight countries: Brazil, Cuba, France, Hungary, India, Japan, Romania and Spain. The book is intended for use in graduate courses on applied computation, applied mathematics, and engineering, where tools like computational intelligence and numerical methods are applied to the solution of real-world problems in emerging areas of engineering.
Nonlinear Approaches in Engineering Applications by Reza N. Jazar,Liming Dai Pdf
This book focuses on the latest applications of nonlinear approaches in engineering and addresses a range of scientific problems. Examples focus on issues in automotive technology, including automotive dynamics, control for electric and hybrid vehicles, and autodriver algorithm for autonomous vehicles. Also included are discussions on renewable energy plants, data modeling, driver-aid methods, and low-frequency vibration. Chapters are based on invited contributions from world-class experts who advance the future of engineering by discussing the development of more optimal, accurate, efficient, cost, and energy effective systems. This book is appropriate for researchers, students, and practising engineers who are interested in the applications of nonlinear approaches to solving engineering and science problems. Presents a broad range of practical topics and approaches; Explains approaches to better, safer, and cheaper systems; Emphasises automotive applications, physical meaning, and methodologies.
Intelligent System Solutions for Auto Mobility and Beyond by Carolin Zachäus,Gereon Meyer Pdf
This book gathers papers from the 23rd International Forum on Advanced Microsystems for Automotive Applications (AMAA 2020) held online from Berlin, Germany, on May 26-27, 2020. Focusing on intelligent system solutions for auto mobility and beyond, it discusses in detail innovations and technologies enabling electrification, automation and diversification, as well as strategies for a better integration of vehicles into the networks of traffic, data and power. Further, the book addresses other relevant topics, including the role of human factors and safety issues in automated driving, solutions for shared mobility, as well as automated bus transport in rural areas. Implications of current circumstances, such as those generated by climate change, on the future development of auto mobility, are also analysed, providing researchers, practitioners and policy makers with an authoritative snapshot of the state-of-the-art, and a source of inspiration for future developments and collaborations.
Artificial Intelligence (AI) is undoubtedly playing an increasingly significant role in automobile technology. In fact, cars inhabit one of just a few domains where you will find many AI innovations packed into a single product. AI for Cars provides a brief guided tour through many different AI landscapes including robotics, image and speech processing, recommender systems and onto deep learning, all within the automobile world. From pedestrian detection to driver monitoring to recommendation engines, the book discusses the background, research and progress thousands of talented engineers and researchers have achieved thus far, and their plans to deploy this life-saving technology all over the world.
Virtual and Augmented Reality for Automobile Industry: Innovation Vision and Applications by Aboul Ella Hassanien,Deepak Gupta,Ashish Khanna,Adam Slowik Pdf
This book presents the augmented reality (AR) and virtual reality (VR) automotive applications. It unites automobile with a leading technology i.e. augmented and virtual reality and uses the advantages of the latter to solve the problems faced by the former. The book highlights the reasons for the growing abundance and complexity in this sector. Virtual and augmented reality presents a powerful engineering tool that finds application in various engineering fields. It brings new possibilities that result is increasing of productivity and reliability of production, quality of products and processes. The book further illustrates the possible challenges in its applications and suggests ways to overcome them. The book includes nine chapters focusing on automobile collision avoidance, self-driving cars, autonomous vehicles, navigation systems, and many more applications.
Artificial Intelligence for Digitising Industry – Applications by Ovidiu Vermesan Pdf
This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment. This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation. The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin. AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection. The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport. This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.
Information Security of Intelligent Vehicles Communication by Madhusudan Singh Pdf
This book highlights cyber-security overview, perspectives, and challenges that affect advanced Vehicular technology. It considers vehicular security issues and possible solutions, with the aim of providing secure vehicle-to-vehicle, vehicle-to-infrastructure and inside-of-vehicle communication. This book introduces vehicle cryptography mechanism including encryption and decryption approaches and cryptography algorithms such as symmetric and asymmetric cryptography, Hash functions and Digital Signature certificates for modern vehicles. It discusses cybersecurity structure and provides specific security challenges and possible solutions in Vehicular Communication such as vehicle to vehicle communication, vehicle to Infrastructure and in-vehicle communciation. It also presents key insights from security with regards to vehicles collaborative information technology. The more our vehicles become intelligent, the more we need to work on safety and security for vehicle technology. This book is of interest to automotive engineers and technical managers who want to learn about security technologies, and for those with a security background who want to learn about basic security issues in modern automotive applications.
Electronic Components and Systems for Automotive Applications by Jochen Langheim Pdf
This volume collects selected papers of the 5th CESA Automotive Electronics Congress, Paris, 2018. CESA is the most important automotive electronics conference in France. The topical focus lies on state-of-the-art automotive electronics with respect to energy consumption and autonomous driving. The target audience primarily comprises industry leaders and research experts in the automotive industry.
Artificial Intelligence for Autonomous Vehicles by Sathiyaraj Rajendran,Munish Sabharwal,Yu-Chen Hu,Rajesh Kumar Dhanaraj,Balamurugan Balusamy Pdf
With the advent of advanced technologies in AI, driverless vehicles have elevated curiosity among various sectors of society. The automotive industry is in a technological boom with autonomous vehicle concepts. Autonomous driving is one of the crucial application areas of Artificial Intelligence (AI). Autonomous vehicles are armed with sensors, radars, and cameras. This made driverless technology possible in many parts of the world. In short, our traditional vehicle driving may swing to driverless technology. Many researchers are trying to come out with novel AI algorithms that are capable of handling driverless technology. The current existing algorithms are not able to support and elevate the concept of autonomous vehicles. This addresses the necessity of novel methods and tools focused to design and develop frameworks for autonomous vehicles. There is a great demand for energy-efficient solutions for managing the data collected with the help of sensors. These operations are exclusively focused on non-traditional programming approaches and depend on machine learning techniques, which are part of AI. There are multiple issues that AI needs to resolve for us to achieve a reliable and safe driverless technology. The purpose of this book is to find effective solutions to make autonomous vehicles a reality, presenting their challenges and endeavors. The major contribution of this book is to provide a bundle of AI solutions for driverless technology that can offer a safe, clean, and more convenient riskless mode of transportation.
Applications of Computational Intelligence in Data-Driven Trading by Cris Doloc Pdf
“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.
Machine Learning for Robotics Applications by Monica Bianchini,Milan Simic,Ankush Ghosh,Rabindra Nath Shaw Pdf
Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas of applications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book.
Autonomous Vehicles, Volume 1 by Romil Rawat,A. Mary Sowjanya,Syed Imran Patel,Varshali Jaiswal,Imran Khan,Allam Balaram Pdf
AUTONOMOUS VEHICLES Addressing the current challenges, approaches and applications relating to autonomous vehicles, this groundbreaking new volume presents the research and techniques in this growing area, using Internet of Things (IoT), Machine Learning (ML), Deep Learning, and Artificial Intelligence (AI). This book provides and addresses the current challenges, approaches, and applications relating to autonomous vehicles, using Internet of Things (IoT), machine learning, deep learning, and Artificial Intelligence (AI) techniques. Several self-driving or autonomous (“driverless”) cars, trucks, and drones incorporate a variety of IoT devices and sensing technologies such as sensors, gyroscopes, cloud computing, and fog layer, allowing the vehicles to sense, process, and maintain massive amounts of data on traffic, routes, suitable times to travel, potholes, sharp turns, and robots for pipe inspection in the construction and mining industries. Few books are available on the practical applications of unmanned aerial vehicles (UAVs) and autonomous vehicles from a multidisciplinary approach. Further, the available books only cover a few applications and designs in a very limited scope. This new, groundbreaking volume covers real-life applications, business modeling, issues, and solutions that the engineer or industry professional faces every day that can be transformed using intelligent systems design of autonomous systems. Whether for the student, veteran engineer, or another industry professional, this book, and its companion volume, are must-haves for any library.
Computational Intelligence Paradigms by L. C. Jain Pdf
This book features research on the innovative applications of advanced computational intelligence paradigms. Coverage includes architectures of computational intelligence paradigms, knowledge discovery, pattern classification, and gene linkage analysis.
Handbook On Computational Intelligence (In 2 Volumes) by Angelov Plamen Parvanov Pdf
With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of 'digital obesity'. In this century, computational intelligence, such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas — from social sciences, economics and biology, medicine and social networks, to cyber security.The Handbook of Computational Intelligence (in two volumes) prompts readers to look at these problems from a non-traditional angle. It takes a step by step approach, supported by case studies, to explore the issues that have arisen in the process. The Handbook covers many classic paradigms, as well as recent achievements and future promising developments to solve some of these very complex problems. Volume one explores the subjects of fuzzy logic and systems, artificial neural networks, and learning systems. Volume two delves into evolutionary computation, hybrid systems, as well as the applications of computational intelligence in decision making, the process industry, robotics, and autonomous systems.This work is a 'one-stop-shop' for beginners, as well as an inspirational source for more advanced researchers. It is a useful resource for lecturers and learners alike.