Download or read book Deep Learning and Big Data for Intelligent Transportation written by Khaled R. Ahmed and published by Springer Nature. This book was released on 2021-04-10 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today’s technology. Road sensors, UAVs, GPS, CCTV and incident reports are sources of massive amount of data which are crucial to make serious traffic decisions. Herewith this substantial volume and velocity of data, it is challenging to build reliable prediction models based on machine learning methods and traditional relational database. Therefore, this book includes recent research works on big data, deep convolution networks and IoT-based smart solutions to limit the vehicle’s speed in a particular region, to support autonomous safe driving and to detect animals on roads for mitigating animal-vehicle accidents. This book serves broad readers including researchers, academicians, students and working professional in vehicles manufacturing, health and transportation departments and networking companies.

Download or read book Data Analytics for Intelligent Transportation Systems written by Mashrur Chowdhury and published by Elsevier. This book was released on 2017-04-05 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Users will learn how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Includes case studies in each chapter that illustrate the application of concepts covered Presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies Contains contributors from both leading academic and commercial researchers Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications

Download or read book Big Data Analytics and Intelligent Techniques for Smart Cities written by Kolla Bhanu Prakash and published by CRC Press. This book was released on 2021-09-20 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics and Intelligent Techniques for Smart Cities covers fundamentals, advanced concepts, and applications of big data analytics for smart cities in a single volume. This comprehensive reference text discusses big data theory modeling and simulation for smart cities and examines case studies in a single volume. The text discusses how to develop a smart city and state-of-the-art system design, system verification, real-time control and adaptation, Internet of Things, and testbeds. It covers applications of smart cities as they relate to smart transportation/connected vehicle (CV) and intelligent transportation systems (ITS) for improved mobility, safety, and environmental protection. It will be useful as a reference text for graduate students in different areas including electrical engineering, computer science engineering, civil engineering, and electronics and communications engineering. Features: Technologies and algorithms associated with the application of big data for smart cities Discussions on big data theory modeling and simulation for smart cities Applications of smart cities as they relate to smart transportation and intelligent transportation systems (ITS) Discussions on concepts including smart education, smart culture, and smart transformation management for social and societal changes

Download or read book Handbook on Artificial Intelligence and Transport written by Hussein Dia and published by Edward Elgar Publishing. This book was released on 2023-10-06 with total page 649 pages. Available in PDF, EPUB and Kindle. Book excerpt: With AI advancements eliciting imminent changes to our transport systems, this enlightening Handbook presents essential research on this evolution of the transportation sector. It focuses on not only urban planning, but relevant themes in law and ethics to form a unified resource on the practicality of AI use.

Download or read book Big Data Analysis and Deep Learning Applications written by Thi Thi Zin and published by Springer. This book was released on 2018-06-06 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of selected papers from the first International Conference on Big Data Analysis and Deep Learning Applications (ICBDL 2018), and focuses on novel techniques in the fields of big data analysis, machine learning, system monitoring, image processing, conventional neural networks, communication, industrial information, and their applications. Readers will find insights to help them realize more efficient algorithms and systems used in real-life applications and contexts, making the book an essential reference guide for academic researchers, professionals, software engineers in the industry, and regulators of aviation authorities.

Download or read book Big Data Transportation Systems written by Guanghui Zhao and published by World Scientific. This book was released on 2021-07-02 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed as a popular science book on big data analytics in intelligent transportation systems. It aims to provide an introduction to big-data transportation starting from an overview on the development of big data transportation in various countries. This is followed by a discussion on the blueprint strategies of big data transportation which include innovative models, planning, transportation logistics, and application case studies. Finally, the book discusses applications of big data transportation platforms.

Download or read book Explainable Artificial Intelligence for Intelligent Transportation Systems written by Loveleen Gaur and published by Springer Nature. This book was released on 2022-08-08 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transportation typically entails crucial “life-death” choices, delegating crucial decisions to an AI algorithm without any explanation poses a serious threat. Hence, explainability and responsible AI is crucial in the context of intelligent transportation. In Intelligence Transportation System (ITS) implementations such as traffic management systems and autonomous driving applications, AI-based control mechanisms are gaining prominence. Explainable artificial intelligence for intelligent transportation system tackling certain challenges in the field of autonomous vehicle, traffic management system, data integration and analytics and monitor the surrounding environment. The book discusses and inform researchers on explainable Intelligent Transportation system. It also discusses prospective methods and techniques for enabling the interpretability of transportation systems. The book further focuses on ethical considerations apart from technical considerations.

Download or read book Big Data Analytics for Smart Transport and Healthcare Systems written by Saeid Pourroostaei Ardakani and published by Springer Nature. This book was released on 2024-01-04 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to introduce big data solutions in urban sustainability applications—mainly smart transportation and healthcare systems. It focuses on machine learning techniques and data processing approaches which have the capacity to handle/process huge, live, and complex datasets in real-time transportation and healthcare applications. For this, several state-of-the-art data processing approaches including data pre-processing, classification, regression, and clustering are introduced, tested, and evaluated to highlight their benefits and constraints where data is sensitive, real-time, and/or semi-structured.

Download or read book Mobility Patterns Big Data and Transport Analytics written by Constantinos Antoniou and published by Elsevier. This book was released on 2018-11-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications and concepts in mobility analysis and transportation systems. Users will find a detailed, mobility 'structural' analysis and a look at the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications and transportation systems analysis that are related to complex processes and phenomena. This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data's impact on mobility and an introduction to the tools necessary to apply new techniques. The book covers in detail, mobility 'structural' analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data's impact on mobility, and an introduction to the tools necessary to apply new techniques.

Download or read book Smart Transportation written by Guido Dartmann and published by CRC Press. This book was released on 2021-11-10 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a broad overview of the challenges and recent developments in the field of smart mobility and transportation, including technical, algorithmic and social aspects of smart mobility and transportation. It reviews new ideas for services and platforms for future mobility. New concepts of artificial intelligence and the implementation in new hardware architecture are discussed. In the context of artificial intelligence, new challenges of machine learning for autonomous vehicles and fleets are investigated. The book also investigates human factors and social questions of future mobility concepts. The goal of this book is to provide a holistic approach towards smart transportation. The book reviews new technologies such as the cloud, machine learning and communication for fully atomatized transport, catering to the needs of citizens. This will lead to complete change of concepts in transportion.

Download or read book Applications of Machine Learning in Big Data Analytics and Cloud Computing written by Subhendu Kumar Pani and published by CRC Press. This book was released on 2022-09-01 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

Download or read book Urban Informatics written by Wenzhong Shi and published by Springer Nature. This book was released on 2021-04-06 with total page 941 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.

Download or read book Machine Learning and Data Mining in Aerospace Technology written by Aboul Ella Hassanien and published by Springer. This book was released on 2019-07-02 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the ‘eagle eyes’ that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites – which can determine satellites’ current status and predict their failure based on telemetry data – is one of the most important current issues in aerospace engineering. This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.

Download or read book Data Analytics for Smart Cities written by Amir Alavi and published by CRC Press. This book was released on 2018-10-26 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of smart cities is one of the most important challenges over the next few decades. Governments and companies are leveraging billions of dollars in public and private funds for smart cities. Next generation smart cities are heavily dependent on distributed smart sensing systems and devices to monitor the urban infrastructure. The smart sensor networks serve as autonomous intelligent nodes to measure a variety of physical or environmental parameters. They should react in time, establish automated control, and collect information for intelligent decision-making. In this context, one of the major tasks is to develop advanced frameworks for the interpretation of the huge amount of information provided by the emerging testing and monitoring systems. Data Analytics for Smart Cities brings together some of the most exciting new developments in the area of integrating advanced data analytics systems into smart cities along with complementary technological paradigms such as cloud computing and Internet of Things (IoT). The book serves as a reference for researchers and engineers in domains of advanced computation, optimization, and data mining for smart civil infrastructure condition assessment, dynamic visualization, intelligent transportation systems (ITS), cyber-physical systems, and smart construction technologies. The chapters are presented in a hands-on manner to facilitate researchers in tackling applications. Arguably, data analytics technologies play a key role in tackling the challenge of creating smart cities. Data analytics applications involve collecting, integrating, and preparing time- and space-dependent data produced by sensors, complex engineered systems, and physical assets, followed by developing and testing analytical models to verify the accuracy of results. This book covers this multidisciplinary field and examines multiple paradigms such as machine learning, pattern recognition, statistics, intelligent databases, knowledge acquisition, data visualization, high performance computing, and expert systems. The book explores new territory by discussing the cutting-edge concept of Big Data analytics for interpreting massive amounts of data in smart city applications.

Download or read book Smart Mobility and Intelligent Transportation Systems for Commercial and Hazardous Vehicles written by Naga Swetha Pasupuleti and published by CRC Press. This book was released on 2024-11-29 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume considers the use of smart technologies in commercial and hazardous vehicles, looking at the challenges and solutions to transportation issues that can be solved with such intelligent applications as artificial intelligence, Internet of Things, neural networks, blockchain, machine learning, big data, etc. The book illustrates the use these smart technologies for vehicle pedestrian detection, in the planning of smart cities for traffic patterns, for the improvement of transportation power stations, for smart railway cargo management systems, and more.

Download or read book Mobility Patterns Big Data and Transport Analytics written by Constantinos Antoniou and published by Elsevier. This book was released on 2018-11-27 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications and concepts in mobility analysis and transportation systems. Users will find a detailed, mobility ‘structural’ analysis and a look at the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications and transportation systems analysis that are related to complex processes and phenomena. This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data’s impact on mobility and an introduction to the tools necessary to apply new techniques. The book covers in detail, mobility ‘structural’ analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data’s impact on mobility, and an introduction to the tools necessary to apply new techniques. Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field Captures and manages mobility patterns, covering multiple purposes and alternative transport modes, in a multi-disciplinary approach Companion website features videos showing the analyses performed, as well as test codes and data-sets, allowing readers to recreate the presented analyses and apply the highlighted techniques to their own data

Download or read book Deep Learning for Unmanned Systems written by Anis Koubaa and published by Springer Nature. This book was released on 2021-10-01 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not limited to, surveillance, search and rescue, environment monitoring, infrastructure monitoring, self-driving cars, contactless last-mile delivery vehicles, autonomous ships, precision agriculture and transmission line inspection to name just a few. These vehicles will benefit from advances of deep learning as a subfield of machine learning able to endow these vehicles with different capability such as perception, situation awareness, planning and intelligent control. Deep learning models also have the ability to generate actionable insights into the complex structures of large data sets. In recent years, deep learning research has received an increasing amount of attention from researchers in academia, government laboratories and industry. These research activities have borne some fruit in tackling some of the challenging problems of manned and unmanned ground, aerial and marine vehicles that are still open. Moreover, deep learning methods have been recently actively developed in other areas of machine learning, including reinforcement training and transfer/meta-learning, whereas standard, deep learning methods such as recent neural network (RNN) and coevolutionary neural networks (CNN). The book is primarily meant for researchers from academia and industry, who are working on in the research areas such as engineering, control engineering, robotics, mechatronics, biomedical engineering, mechanical engineering and computer science. The book chapters deal with the recent research problems in the areas of reinforcement learning-based control of UAVs and deep learning for unmanned aerial systems (UAS) The book chapters present various techniques of deep learning for robotic applications. The book chapters contain a good literature survey with a long list of references. The book chapters are well written with a good exposition of the research problem, methodology, block diagrams and mathematical techniques. The book chapters are lucidly illustrated with numerical examples and simulations. The book chapters discuss details of applications and future research areas.