Real Time Data Analytics for Large Scale Sensor Data Book

Real Time Data Analytics for Large Scale Sensor Data


  • Author : Himansu Das
  • Publisher : Academic Press
  • Release Date : 2019-08-31
  • Genre: Science
  • Pages : 298
  • ISBN 10 : 9780128182420

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Real Time Data Analytics for Large Scale Sensor Data Excerpt :

Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods for high performance stream processing, adaptively streaming adjustment, uncertainty handling, latency handling, and more. Examines IoT applications, the design of real-time intelligent systems, and how to manage the rapid growth of the large volume of sensor data Discusses intelligent management systems for applications such as healthcare, robotics and environment modeling Provides a focused approach towards the design and implementation of real-time intelligent systems for the management of sensor data in large-scale environments

Demand based Data Stream Gathering  Processing  and Transmission Book

Demand based Data Stream Gathering Processing and Transmission


  • Author : Jonas Traub
  • Publisher : BoD – Books on Demand
  • Release Date : 2021-04-09
  • Genre: Computers
  • Pages : 206
  • ISBN 10 : 9783752671254

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Demand based Data Stream Gathering Processing and Transmission Excerpt :

This book presents an end-to-end architecture for demand-based data stream gathering, processing, and transmission. The Internet of Things (IoT) consists of billions of devices which form a cloud of network connected sensor nodes. These sensor nodes supply a vast number of data streams with massive amounts of sensor data. Real-time sensor data enables diverse applications including traffic-aware navigation, machine monitoring, and home automation. Current stream processing pipelines are demand-oblivious, which means that they gather, transmit, and process as much data as possible. In contrast, a demand-based processing pipeline uses requirement specifications of data consumers, such as failure tolerances and latency limitations, to save resources. Our solution unifies the way applications express their data demands, i.e., their requirements with respect to their input streams. This unification allows for multiplexing the data demands of all concurrently running applications. On sensor nodes, we schedule sensor reads based on the data demands of all applications, which saves up to 87% in sensor reads and data transfers in our experiments with real-world sensor data. Our demand-based control layer optimizes the data acquisition from thousands of sensors. We introduce time coherence as a fundamental data characteristic. Time coherence is the delay between the first and the last sensor read that contribute values to a tuple. A large scale parameter exploration shows that our solution scales to large numbers of sensors and operates reliably under varying latency and coherence constraints. On stream analysis systems, we tackle the problem of efficient window aggregation. We contribute a general aggregation technique, which adapts to four key workload characteristics: Stream (dis)order, aggregation types, window types, and window measures. Our experiments show that our solution outperforms alternative solutions by an order of magnitude in throughput, which prevents expensi

Handbook of Large Scale Distributed Computing in Smart Healthcare Book

Handbook of Large Scale Distributed Computing in Smart Healthcare


  • Author : Samee U. Khan
  • Publisher : Springer
  • Release Date : 2017-08-07
  • Genre: Computers
  • Pages : 635
  • ISBN 10 : 9783319582801

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Handbook of Large Scale Distributed Computing in Smart Healthcare Excerpt :

This volume offers readers various perspectives and visions for cutting-edge research in ubiquitous healthcare. The topics emphasize large-scale architectures and high performance solutions for smart healthcare, healthcare monitoring using large-scale computing techniques, Internet of Things (IoT) and big data analytics for healthcare, Fog Computing, mobile health, large-scale medical data mining, advanced machine learning methods for mining multidimensional sensor data, smart homes, and resource allocation methods for the BANs. The book contains high quality chapters contributed by leading international researchers working in domains, such as e-Health, pervasive and context-aware computing, cloud, grid, cluster, and big-data computing. We are optimistic that the topics included in this book will provide a multidisciplinary research platform to the researchers, practitioners, and students from biomedical engineering, health informatics, computer science, and computer engineering.

Computational Intelligence Applications in Business Intelligence and Big Data Analytics Book

Computational Intelligence Applications in Business Intelligence and Big Data Analytics


  • Author : Vijayan Sugumaran
  • Publisher : CRC Press
  • Release Date : 2017-06-26
  • Genre: Computers
  • Pages : 362
  • ISBN 10 : 9781351720250

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Computational Intelligence Applications in Business Intelligence and Big Data Analytics Excerpt :

There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.

Service Oriented Computing Book

Service Oriented Computing


  • Author : Sami Yangui
  • Publisher : Springer Nature
  • Release Date : 2019-10-25
  • Genre: Computers
  • Pages : 583
  • ISBN 10 : 9783030337025

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Service Oriented Computing Excerpt :

This book constitutes the proceedings of the 17th International Conference on Service-Oriented Computing, ICSOC 2019, held in Toulouse, France, in October 2019. The 28 full and 12 short papers presented together with 7 poster and 2 invited papers in this volume were carefully reviewed and selected from 181 submissions. The papers have been organized in the following topical sections: Service Engineering; Run-time Service Operations and Management; Services and Data; Services in the Cloud; Services on the Internet of Things; Services in Organizations, Business and Society; and Services at the Edge.

Smart Grid Using Big Data Analytics Book

Smart Grid Using Big Data Analytics


  • Author : Robert C. Qiu
  • Publisher : John Wiley & Sons
  • Release Date : 2017-04-17
  • Genre: Technology & Engineering
  • Pages : 632
  • ISBN 10 : 9781118494059

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Smart Grid Using Big Data Analytics Excerpt :

This book is aimed at students in communications and signal processing who want to extend their skills in the energy area. It describes power systems and why these backgrounds are so useful to smart grid, wireless communications being very different to traditional wireline communications.

Machine Learning for Intelligent Decision Science Book

Machine Learning for Intelligent Decision Science


  • Author : Jitendra Kumar Rout
  • Publisher : Springer Nature
  • Release Date : 2020-04-02
  • Genre: Technology & Engineering
  • Pages : 209
  • ISBN 10 : 9789811536892

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Machine Learning for Intelligent Decision Science Excerpt :

The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.

Artificial Intelligence for the Internet of Health Things Book

Artificial Intelligence for the Internet of Health Things


  • Author : K. Shankar
  • Publisher : CRC Press
  • Release Date : 2021-05-10
  • Genre: Computers
  • Pages : 216
  • ISBN 10 : 9781000374292

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Artificial Intelligence for the Internet of Health Things Excerpt :

This book discusses research in Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in design, implementation, and optimization of challenging healthcare solutions. This book features a wide range of topics such as AI techniques, IoT, cloud, wearables, and secured data transmission. Written for a broad audience, this book will be useful for clinicians, health professionals, engineers, technology developers, IT consultants, researchers, and students interested in the AI-based healthcare applications. Provides a deeper understanding of key AI algorithms and their use and implementation within the wider healthcare sector Explores different disease diagnosis models using machine learning, deep learning, healthcare data analysis, including machine learning, and data mining and soft computing algorithms Discusses detailed IoT, wearables, and cloud-based disease diagnosis model for intelligent systems and healthcare Reviews different applications and challenges across the design, implementation, and management of intelligent systems and healthcare data networks Introduces a new applications and case studies across all areas of AI in healthcare data K. Shankar (Member, IEEE) is a Postdoctoral Fellow of the Department of Computer Applications, Alagappa University, Karaikudi, India. Eswaran Perumal is an Assistant Professor of the Department of Computer Applications, Alagappa University, Karaikudi, India. Dr. Deepak Gupta is an Assistant Professor of the Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.

Big Data Management and Processing Book

Big Data Management and Processing


  • Author : Kuan-Ching Li
  • Publisher : CRC Press
  • Release Date : 2017-05-19
  • Genre: Computers
  • Pages : 469
  • ISBN 10 : 9781498768085

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Big Data Management and Processing Excerpt :

From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies." ---Sartaj Sahni, University of Florida, USA "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields. --Hai Jin, Huazhong University of Science and Technology, China Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems. The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges an

Maritime Technology and Engineering III Book

Maritime Technology and Engineering III


  • Author : Carlos Guedes Soares
  • Publisher : CRC Press
  • Release Date : 2016-12-01
  • Genre: Technology & Engineering
  • Pages : 1208
  • ISBN 10 : 9781498795937

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Maritime Technology and Engineering III Excerpt :

Maritime Technology and Engineering 3 is a collection of papers presented at the 3rd International Conference on Maritime Technology and Engineering (MARTECH 2016, Lisbon, Portugal, 4-6 July 2016). The MARTECH Conferences series evolved from biannual national conferences in Portugal, thus reflecting the internationalization of the maritime sector. The keynote lectures and the papers, making up nearly 150 contributions, came from an international group of authors focused on different subjects in a variety of fields: Maritime Transportation, Energy Efficiency, Ships in Ports, Ship Hydrodynamics, Ship Structures, Ship Design, Ship Machinery, Shipyard Technology, afety & Reliability, Fisheries, Oil & Gas, Marine Environment, Renewable Energy and Coastal Structures. This book will appeal to academics, engineers and professionals interested or involved in these fields.

Advanced Nanomaterials for Point of Care Diagnosis and Therapy Book

Advanced Nanomaterials for Point of Care Diagnosis and Therapy


  • Author : Sushma Dave
  • Publisher : Elsevier
  • Release Date : 2022-03-25
  • Genre: Technology & Engineering
  • Pages : 594
  • ISBN 10 : 9780323900669

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Advanced Nanomaterials for Point of Care Diagnosis and Therapy Excerpt :

Advanced Nanomaterials for Point of Care Diagnosis and Therapy provides an overview of technological and emerging novel trends in how point-of-care diagnostic devices are designed, miniaturized built, and delivered at different healthcare set ups. It describes the significant technological advances in fundamental diagnostic components and recent advances in fully integrated devices designed for specific clinical use. The book covers state-of-the-art fabrication of advances materials with broad spectrum therapeutic applications. It includes drug delivery, biosensing, bioimaging and targeting, and outlines the development of inexpensive, effective and portable in vitro diagnostics tools for any purpose that can be used onsite. Sections also discuss drug delivery, biosensing, bioimaging and targeting and various metal, metal oxide and non-metal-based nanomaterials that are developed, surface modified, and are being explored for diagnosis, targeting, drug delivery, drug release and imaging. The book concludes with current needs and future challenges in the field. Outlines the needs and challenges of point-of-care diagnostics Describes the fundamentals of application of nanomaterials as interesting building blocks for biosensing Overviews the different detection methods offered by using nanomaterials Explains the advantages and drawbacks of nanomaterial-based sensing strategies Describes the opportunities offered by technology as a cost-efficient biosensing platform

Data Analytics for Smart Cities Book

Data Analytics for Smart Cities


  • Author : Amir Alavi
  • Publisher : CRC Press
  • Release Date : 2018-10-26
  • Genre: Computers
  • Pages : 240
  • ISBN 10 : 9780429786631

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Data Analytics for Smart Cities 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,

Machine Learning and Data Science in the Oil and Gas Industry Book

Machine Learning and Data Science in the Oil and Gas Industry


  • Author : Patrick Bangert
  • Publisher : Gulf Professional Publishing
  • Release Date : 2021-03-04
  • Genre: Computers
  • Pages : 306
  • ISBN 10 : 9780128209141

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Machine Learning and Data Science in the Oil and Gas Industry Excerpt :

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful Gain practical understanding of machine learning used in oil and gas operations through contributed case studies Learn change management skills that will help gain confidence in pursuing the technology Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)

Advanced Technologies for Humanity Book

Advanced Technologies for Humanity


  • Author : Rajaa Saidi
  • Publisher : Springer Nature
  • Release Date : 2022-01-29
  • Genre: Technology & Engineering
  • Pages : 555
  • ISBN 10 : 9783030941888

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Advanced Technologies for Humanity Excerpt :

This book gathers the proceedings of the International Conference on Advanced Technologies for Humanity (ICATH’2021), held on November 26-27, 2021, in INSEA, Rabat, Morocco. ICATH’2021 was jointly co-organized by the National Institute of Statistics and Applied Economics (INSEA) in collaboration with the Moroccan School of Engineering Sciences (EMSI), the Hassan II Institute of Agronomy and Veterinary Medicine (IAV-Hassan II), the National Institute of Posts and Telecommunications (INPT), the National School of Mineral Industry (ENSMR), the Faculty of Sciences of Rabat (UM5-FSR), the National School of Applied Sciences of Kenitra (ENSAK) and the Future University in Egypt (FUE). ICATH’2021 was devoted to practical models and industrial applications related to advanced technologies for Humanity. It was considered as a meeting point for researchers and practitioners to enable the implementation of advanced information technologies into various industries. This book is helpful for PhD students as well as researchers. The 48 full papers were carefully reviewed and selected from 105 submissions. The papers presented in the volume are organized in topical sections on synergies between (i) smart and sustainable cities, (ii) communication systems, signal and image processing for humanity, (iii) cybersecurity, database and language processing for human applications, (iV) renewable and sustainable energies, (V) civil engineering and structures for sustainable constructions, (Vi) materials and smart buildings and (Vii) Industry 4.0 for smart factories. All contributions were subject to a double-blind review. The review process was highly competitive. We had to review 105 submissions from 12 countries. A team of over 100 program committee members and reviewers did this terrific job. Our special thanks go to all of them.

Managing and Mining Sensor Data Book

Managing and Mining Sensor Data


  • Author : Charu C. Aggarwal
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-01-15
  • Genre: Computers
  • Pages : 534
  • ISBN 10 : 9781461463092

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Managing and Mining Sensor Data Excerpt :

Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.